System and method for determining ethicality of media sources and advertising of media sources

Abstract

A method and a system of operating an ethical media index scoring engine to evaluate the ethicality of a digital media advertising domain. The method including receiving data via a communications interface from servers and analysing the data for missing values. If values are missing, the method further includes replacing the missing values in the data based on a schema and updating the confidence score value. Once missing values have been replaced, the method includes normalizing the data based on the schema with weighting factors via a scoring module. The method also includes aggregating a normalized data into an ethical media index score via the scoring module and displaying the ethical media index score on a graphical user interface to aid a user in making a decision whether to advertise on the domain.

Description

SYSTEM AND METHOD FOR DETERMINING ETHICALITY OF MEDIA SOURCES AND ADVERTISING OF MEDIA SOURCESFIEED OF INVENTION

[0001] The present invention relates generally to a system and method for determining the ethicality of media sources or platforms for digital media advertising, and more specifically to a system and method for analyzing media sources or platforms to determine their ethicality and moral standing.BACKGROUND OF THE INVENTION

[0002] Advertisers and media buyers are increasingly attempting to combine advertising performance (e.g, driving sales) with Ethical Media investment. “Ethical Media” generally means media (e.g. any means of mass communication such as broadcasting, publishing, and the internet) that is recognized as “ethical”, such as by taking factors such as sustainability, accuracy, diversity, etc. into account when planning and buying media advertising. Within digital media advertising (“DMA”) (e.g. placing advertising campaigns on websites and apps) there are currently various ways to estimate the ethicality of media in which DMA is or will be placed, generally referred to as “Ethical Media”. The more accurately that specific media can be determined to be ethical media, the more desirable such media would be to a DMA that values such ethicality. However, there is currently no way to accurately, reliably and consistently assess the ethicality of media, or a domain. Nor is there any way to reliably compare the ethicality of media sources, as the estimates wildly vary in both reliability and accuracy. For example, a DMA buyer could measure the carbon emissions of delivering an advertising campaign, through factors such as device usage and data transfer; or they could measure how the media owners place advertising campaigns, and how they operate at a corporate level by looking at the types of ESG criteria typically used in financial markets. However, these represent individual data points and there has been no solution that gives a rounded, robust and holistic measurement of how ethical different websites and applications are.SUMMARY OF INVENTION

[0003] According to various aspects of the present invention, there is provided a method of operating an ethical media index scoring engine to evaluate the ethicality of a digital mediaadvertising domain. The method includes receiving data via a communications interface from a plurality of servers and analysing the data for missing values. If values are missing, the method includes replacing the missing values in the data based on a schema and updating a confidence score value. After replacing the missing values, or if no values are missing, the method further includes normalizing the data based on the schema with weighting factors via a scoring module and aggregating a normalized data into an ethical media index score via the scoring module. In addition, the method includes displaying the ethical media index score on a graphical user interface to aid a user in making a decision whether to advertise on the domain.

[0004] In one embodiment, analysing the data for missing values includes determining if values from the data are missing or incomplete.

[0005] In yet another embodiment, replacing the missing values in the data based on the schema includes determining a type of metric of the missing value, determining a replacement value based on the type of metric from the schema, and substituting the missing value with the replacement value.

[0006] In yet another further embodiment, replacing the missing values in the data based on the schema includes determining a type of metric of the missing value and determining a replacement function based on the type of metric from the schema. In addition, the method includes calculating a replacement value to substitute for the missing value using the replacement function and substituting the missing value with the replacement value.

[0007] In yet another embodiment, replacing the missing values in the data based on the scheme includes determining a type of metric of the missing value and determining a replacement coding module based on the type of metric from the schema. In addition, the method includes determining a replacement value to substitute for the missing value using the replacement coding module and substituting the missing value with the replacement value.

[0008] In another embodiment, updating the confidence score value includes determining a type of metric of the missing value and determining the weight of the missing value based on the type of metric from the schema. In addition, the method includes calculating a second confidence score value by reducing the first confidence score value by the weight of the missing value.

[0009] In a further embodiment, normalizing the data based on the schema with weighting factors via the scoring module includes determining a type of metric of the data being normalized and determining the weight of the data based on the type of metric from the schema. The method further includes calculating the normalized data based on the retrieved weight from the schema.

[0010] In another embodiment, aggregating a normalized data into an ethical media index score includes aggregating the normalized data of a plurality of types of metrics.

[0011] The plurality of types of metrics may include at least a corporate score, a content score and an advertising score.

[0012] In yet another embodiment, the method may further include analyzing the ethical media index score for an advertising portfolio of multiple domains to aid a user in determining whether to add or remove domains from the advertising portfolio.

[0013] According to various aspects of the present invention, there is provide a system for evaluating ethicality of a domain. The system includes a communications interface connected to a network, wherein the communications interface is configured to receive data from a plurality of servers. The system also includes a memory storage unit. The memory storage unit includes a schema providing instructions on replacing missing values in the data received from the plurality of servers, updating a confidence score value and instructions for weighting and normalizing the data. The memory storage unit also includes a scoring module. The system further includes a processor connected to the communications interface and the memory storage unit. The processor configured to normalize the data with weighting factors based on the schema via the scoring module and aggregate the data into an ethical media index score via the scoring module. The processor also configured to display the ethical media index score on a graphical user interface to aid a user in making a decision whether to advertise on the domain.

[0014] In another embodiment, the instructions of the schema on replacing missing values in the data includes instructions for replacing missing or incomplete data.

[0015] In yet another embodiment, the schema includes a type of metric and a replacement value based on the type of metric, where if values are missing or incomplete from the data received from the plurality of servers. The processor may further be configured to determine the type ofmetric of the missing value. The processor may also be further configured to determine the replacement value based on the type of metric from the schema and substitute the missing value with the replacement value.

[0016] In another embodiment, the schema includes a type of metric and a replacement function based on the type of metric, where if values are missing or incomplete from the data received from the plurality of servers. The processor may further be configured to determine the type of metric of the missing value and determine the replacement function based on the type of metric from the schema. The processor may also be configured to calculate a replacement value using the replacement function and substitute the missing value with the replacement value.

[0017] In yet another embodiment, the schema includes a type of metric and a replacement coding module based on the type of metric, where if values are missing or incomplete from the data received from the plurality of servers. The processor may further be configured to determine the type of metric of the missing value and determine the replacement coding module based on the type of metric from the schema. The processor may also be configured to determine a replacement value using the replacement coding module and substitute the missing value with the replacement value.

[0018] In yet another embodiment, the schema includes a type of metric and a weight for each type of metric, where if values are missing or incomplete from the data received from the plurality of servers. The processor may further be configured to determine the type of metric of the missing value, determine the weight of the missing value based on the type of metric from the schema, and calculating a new confidence score value by reducing the prior confidence score value by the weight of the missing value.

[0019] In another embodiment, the schema includes the type of metric and a weight for each type of metric. The processor may be further configured to normalize the data with weighting factors based on the schema via the scoring module. This may include the processor configured to determine the type of metric of the data being normalized, determine the weight of the data based on the type of metric from the schema and calculate the normalized data based on the retrieved weight from the schema.

[0020] In yet another embodiment, the processor may be configured to aggregate the data into an ethical media index score includes aggregating the normalized data of a plurality of types of metrics.

[0021] The plurality of types of metrics may include at least a corporate score, a content score and an advertising score.

[0022] In yet another embodiment, the memory storage unit further includes an advertising portfolio of multiple domains, wherein the processor may be further configured to analyze the ethical media index score for the advertising portfolio of multiple domains to aid a user in determining whether to add or remove domains from the advertising portfolio.BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The embodiments of the present invention shall be more clearly understood with reference to the following detailed description of the embodiments of the invention taken in conjunction with the accompanying drawings, in which:

[0024] FIG. 1 depicts an example system for analyzing and determining the ethicality of domains and media sources;

[0025] FIG. 2 depicts an example method for determining the ethicality of domains and media platforms in accordance with the example system of FIG. 1;

[0026] FIG. 3 depicts a continuation of the example method of FIG. 2;

[0027] FIG. 4 depicts an example graphical user interface showcasing the ethical media index score, the advertising score, the content score, the corporate score and the confidence level of a list of domains and media platforms;

[0028] FIG. 5 depicts an example graphical user interface showcasing detailed information regarding a specific domain or media source;

[0029] FIG. 6 depicts an example graphical user interface showcasing a user’s advertising campaign with the relevant ethical media index scores;

[0030] FIG. 7 depicts an example graphical user interface showcasing advertising information and ethical media index score of specific domains and media platforms;

[0031] FIG. 8 depicts an example schema stored in memory for modifying data; and

[0032] FIG. 9 depicts an example ethical index score.DESCRIPTION OF THE PREFERRED EMBODIMENTS OF THE INVENTION

[0033] The description, which follows, and the embodiments described therein are provided by way of illustration of an example, or examples of particular embodiments of principles and aspects of the present invention. These examples are provided for the purposes of explanation and not of limitation, of those principles of the invention. In the description that follows, like parts are marked throughout the specification and the drawings with the same respective reference numerals.

[0034] By way of general overview, there is provided a system and method of determining the ethicality of a domain or media source for DMA. Hereinafter, the terms “domain”, “media source”, “media platform” may be used interchangeably. In at least some embodiments, the advantage of the system allows for users to determine whether or the extend or degree to which one or more domains or media source / platform may be considered ethical media (e.g. an ethical source) when selecting domains for advertising. Furthermore, the system allows users to compare the ethicality of domains and media platforms against each other.

[0035] A person skilled in the relevant art would understand that the term “ethical” or “ethicality”, when used in association with digital media, refers to digital media that is generally considered to be ethical or high on a scale of ethicality (e.g. highly ethical) when assessed under a number of criteria such as accuracy (e.g. accuracy of information from all sources avoiding error, when mistakes are made, they are corrected, etc.), reliability of sources, credibility, avoiding bias (e.g. distinguishing between news and advertising), information gathering (e.g. avoid undercover or other surreptitious methods of gathering information), taking into account environmental, social and other factors, avoiding conflict of interests, etc. A person skilled in the relevant art would understand that the term “ethical media” refers to media that is generally considered to be ethical or high on a rating of ethicality.

[0036] More specifically, the system includes an ethical media index scoring engine 104 and various sources of data in databases 148, 152, and 156. The ethical media index scoring engine 104 requests and receives data from various sources, and then modifies the data. In a preferred embodiment, the ethical media index scoring engine 104 may also compensate where data or information is incomplete (e.g. compensating for any missing or incomplete data). Once all data has been gathered, a corporate score 904, an advertising score 908 and a content score 912 can be created, even where there is incomplete or missing data. Each of these scores 904, 908 and 912 can indicate the ethicality of the DMA domain from a specific perspective. More specifically, the corporate score 904, in a preferred embodiment, may measure the environmental, social and governance (ESG) metrics of the company that operates the domain or the media source / platform. The advertising score 908 measures the carbon emission and level of wastage in serving un-needed advertising from the domain or media source. The content score 912 measures the ethics of the content provided. The corporate score 904, advertising score 908 and content score 912 may then be merged by the processor 112 of the ethical media index scoring engine 104 into an ethical media index score 900 and displayed on a graphical user interface of a client terminal 144 for a user to aid in their selection of domains and media platforms for advertising, or evaluate their already selected partners for their ethicality to determine whether to continue partnerships with said domains and media platforms.

[0037] FIG. 1 depicts a system 100 for determining the ethicality of domains. More specifically, system 100 includes ethical media index scoring engine 104 communicating with databases 148, 152 and 156 via wireless access network (“WAN”) 140. More specifically, ethical media index scoring engine 104 (also referred to herein as server 104) includes communications interface 108, processor 112 and memory 116, wherein ethical media index scoring engine 104 queries and receives data from corporate databases 148, advertising databases 152, and content databases 156. Data received from databases 148, 152, and 156 may then be modified and analyzed by ethical media index scoring engine 104, and then displayed on a graphical user interface on client terminal 144. The analyzed data on the graphical user interface may then be used by the user in decision making with respect to advertising. Components of system 100 will discussed further in detail below.

[0038] Ethical media index scoring engine 104 includes a processor 112 interconnecting a memory 116 and a communications interface 108. The processor 112 can include a centralprocessing unit (CPU), a graphics processing unit (GPU), a microcontroller, a microprocessor, a processing core, a field-programmable gate array (FPGA), or similar. In some embodiments, the processor 112 can include multiple cooperating processors. The processor 112 can cooperate with non-transitory computer readable medium, such as the memory 116 to execute instructions to realize the functionality discussed herein.

[0039] Memory 116 can include a combination of volatile memory (e.g. Random Access Emmery or RAM) and non-volatile memory (e.g. non-volatile random-access memory, read only memory or ROM, Electrically Erasable Programmable Read Only memory or EEPROM, flash memory). All or some of the memory 116 can be integrated with processor 112. Memory 116 stores computer reasonable instructions for execution by processor 112.

[0040] It will now be apparent that each element of memory 116 can be carried out by the processor 112 executing operations. In other words, functionality described below as being carried out by a module of memory 116 or a module of ethical media index scoring engine 104 can be based on any known server environment.

[0041] In some embodiments, memory 116 stores a plurality of computer-readable data and programming instructions, accessible by processor 112, in the form of software objects, such as various applications, queries or types of data for use during the execution of those applications. In particular, the execution of the instructions in memory 116 by processor 112 queries or requests data from corporate databases 148, advertising databases 152, and content databases 156, and receives said data via communications interface 108. In addition, the execution of the instructions in memory 116 also determines if any data points are missing or incomplete from the retrieved data, compensates for the missing or incomplete data and analyzes the data. Furthermore, the execution of the instructions in memory 116 by processor 112 provides the resulting analyzed results in a graphical user interface for a user to view and make decisions upon. The person skilled in the art will now recognize the various forms of computer-readable programming instructions stored in memory 116 can be executed by processor 112 as applications or queries.

[0042] In at least some embodiments, memory 116 stores corporate scoring module 120. The execution of corporate scoring module 120 by processor 112 allows for the modification and normalization of corporate data received from corporate databases 148, and for the compensation of any missing or incomplete data points from the corporate data received from corporate databases 148. The corporate scoring module 120 also provides instructions to processor 112 to create the corporate score 904 for a specified domain.

[0043] The corporate score 904 may be a measurement of the ESG of the corporations that owns and operates the domain being measured. Web domains are influenced by, and reward, the companies that own them. As such, the measurement of a company’s ESG can be a factor of a web domains ethicality, and hence impacts a domain’s ethical index score. The corporate score 904 aids media buyers that engage with media owners through the purchasing and placing of ads, how ethical the media owner is operating at company level. This information is important as the advertising placed by the media buyers with the media owners is funding the media owners. As such, even in examples where a business provides above-average content on their websites, if the business provides low wages to their staff, or mistreats their staff, the business is penalized through the corporate score 904. Additionally, if the business owns several domains, the corporate score 904 may be consistent, as the business itself is the same.

[0044] Referring to FIG. 9, in one embodiment, the corporate score 904 may include several metrics. Each metric is a specific measurement and is provided to ethical media index scoring engine 104 as a data point. In the current embodiment, the corporate score 904 includes at least an environment metric 916, a social metric 920, a governance metric 924, an employee metric 928 and a diversity metric 932.

[0045] The environment metric 916, social metric 920 and governance metric 924 provide the ESG component of the ethical media index score 900. Specifically, the environment metric 916, social metric 920, and governance metric 924 measures the ESG of the company that owns the specified domain being measured, which directly impacts the ethicality of the domain. Furthermore, the environment metric 916, social metric 920 and governance metric 924 allow for an increased granular perspective into the measurement of the specified domain and company. This may include factors including, but not limited to, community development and philanthropy,human rights and supply chains, energy and climate change, environment policy and reporting, resource management, the actions and / or the involvement of the board, leadership ethics, the use of green energy for the hosting of websites or domains, media distribution emissions (emissions of serving web pages to users), diversity, and labour rights. The higher the environmental metric 916, social metric 920 and governance metric 924, the higher the ethical media index score 900. More specifically, in the one embodiment, the environmental metric 916, social metric 920 and governance metric 924 are directly proportional to the ethical media index score 900.

[0046] The employee metric 928 measures employee satisfaction and includes, but is not limited to, factors such as whether employees are treated fairly, the compensation of employees, and whether employees receive benefits. The higher the employee metric 928, the higher the ethical media index score 900. More specifically, in the current embodiment, the employee metric 928 is directly proportional to the ethical media index score 900.

[0047] Diversity may be considered important, as it is included within the United Nation’s definition of sustainability. Specifically, the Sustainability Development Goals of the United Nations (which will be further discussed below) includes goals such as reduced inequalities and gender equality. The diversity metric 932 measures the employee diversity within the company that owns the specified domain being measured. In addition, historically, advertising budgets have not been spent with minority owned businesses, or advertising campaigns have excluded minority groups all together. Advertisers are now looking to increase the advertising budget being spent on minority owned businesses and / or are looking for additional channels for advertising campaigns to be more inclusive of minorities. The measurement of a diversity metric 932 also aids in determining whether a company has been inclusive of minorities. The more diverse the employees are of the company, the more inclusive of advertising with minority owned businesses, and / or the more channels directed towards minorities, the higher the diversity metric 932, which leads to an increase in the ethical media index score 900. More specifically, in the current embodiment, the diversity metric 932 is directly proportional to the ethical media index score 900.

[0048] In another embodiment (not shown), an ownership profile metric may also be included as part of corporate score 904. The ownership profile metric scores the owners, shareholders, officers and / or directors of the corporation that owns the domain or media sourcebeing scored. For example, the diversity, ethnic backgrounds, gender parity and sexual orientation of the owners, shareholders, officers and / or directors of the corporation are evaluated and scored. The greater the diversity in ownership, the greater the ownership profile metric, which leads to an increase in ethical media index score 900. In calculating the ownership profile metric, websites are crawled for ownership information and then for diversity, gender, etc. The websites may be crawled using processor 112 in conjunction with a large language model, so as to capture different variations in presenting the data on domains. A person skilled in the art will recognize different configurations and methods of crawling a domain or website for information. In alternate embodiments, the data from the websites may also be vetted manually to ensure accuracy.

[0049] In yet another embodiment, the website accessibility signals metric (not shown) may also contribute to corporate score 904. Website accessibility signals include features that help users with disabilities to access and use websites or domains. Website accessibility signals include, but are not limited to, keyboard navigation, closed captures, and colour contrast. A person skilled in the art will recognize the different website accessibility signals available. The greater the availability and number of website accessibility signals or tools to aid in users with disabilities in other media sources, the higher the website accessibility signal score. The website accessibility score may be calculated based on manual determination of the availability of website accessibility signals, or data regarding the domain may be received from an external database or source. Specifically, the website accessibility signals metric is directly proportional to ethical media index score 900.

[0050] In yet another embodiment, the website data security metric (not shown) may also contribute to corporate score 904. Website data security includes determining the robustness of a domain infrastructure, including, but not limited to performing a WHOIS domain check, a SSL vulnerability check, a SSL certificate validation, performing a mail exchanger (MX) record configuration analysis, a nameserver (NS) record configuration test, and a malware database check. The results from said tests may be accessed via API from a third party database, and a score may be assigned to create the website data security metric. In the current embodiment, the higher the website data security metric, the more secure the website is. Specifically, the website data security metric is directly proportional to ethical media index score 900.

[0051] A person skilled in the art will recognize that there are other additional metrics that may be used to measure the ethicality of the company owning the domain, and that any number of the above-mentioned metrics or other metrics may be included in the corporate score 904.

[0052] Returning to FIG.1 , in a preferred embodiment, as instructed by corporate scoring module 120, processor 112 may query or request the corporate data of at least one domain from corporate databases 148 via communications interface 108 over WAN 140. In the current embodiment, the request or query may be made to a single corporate database 148 that is external to ethical media index scoring engine 104. It will occur to a person skilled in the art that the request or query may be made to more than one database, and that said database or databases may be either external to ethical media index scoring engine 104, internal within ethical media index scoring engine 104, or a hybrid of both. A person skilled in the art will also recognize that any query to corporate databases 148 external to ethical media index scoring engine 104 may be via communications interface 108 and WAN 140, and that any query to corporate databases 148 that may be internal to ethical media index scoring engine 104 may be within memory 116.

[0053] Upon receiving the requested corporate data or metrics from corporate database 148 via WAN 140 and communications interface 108, processor 112 may then determine if there are any missing or incomplete metrics or data for each domain. If there are missing or incomplete metrics or data, then processor 112 may refer to schema 136 to determine next actions to compensate for the missing or incomplete metrics data. This will be further discussed below.

[0054] Once processor 112 has compensated for the missing or incomplete metrics / data, each metric may be further modified based on schema 136. Specifically, each metric may be normalized and then weighted based on information provided from schema 136. This will also be further discussed below.

[0055] Corporate scoring module 120 may then provide instructions to processor 112 to merge the relevant metrics or data to create corporate score 904. In the current embodiment, corporate scoring module 120 provides instructions to processor 112 to merge the environment metric 916, the social metric 920, the governance metric 924, the employee metric 928 and the diversity metric 932 to create corporate score 904. A person skilled in the art will recognize thatany number of the abovementioned metrics or other metrics related to the company owning the domain may be merged to create corporate score 904.

[0056] In at least some embodiments, memory 116 stores advertising scoring module 124. Similar to the corporate scoring module 120, the execution of advertising scoring module 124 by processor 112 allows for the modification and normalization of advertising data received from advertising databases 152, and for the compensation of any missing or incomplete data points or metrics from the advertising data received from advertising databases 152. The advertising scoring module 124 also provides instructions to processor 112 to create the advertising score 908 for a specified domain.

[0057] The advertising score 908 (also referred to herein as consumption score 908) is a measurement of internet energy consumption of the domain. Digital advertising impacts climate change through energy use. The Internet accounts for 3% of global greenhouse gas emissions according to Freitag, et al., 2021 https: / / www.sciencedirect.com / science / article / pii / S2666389921001884, and advertising is a substantial portion of said greenhouse gas emissions. To that end, the advertising score 908 reflects the carbon emissions emitted through advertising transactions of the domain and the level of wastage in serving un-needed advertising (also referred to herein as invalid traffic).

[0058] Referring to FIG. 9, the advertising score 908 may include carbon emissions display metric 936, carbon emissions video metric 940 and invalid traffic metric 944.

[0059] Carbon emissions are measured for display advertising as carbon emissions display metric 936, and carbon emissions for video advertising are measured as carbon emissions video metric 940. Carbon emissions display metric 936 and carbon emissions video metric 940 are measured based on the grams of CO2 per 1,000 delivered ad impressions for the domain. This includes transmission and device emissions, including emissions from a web page and associated adverts being delivered (Content Management System (CMS), Content Delivery Network (CDN), hosting) and consumed at a user’s device (electrical grid mix at the time the ad is served). The electrical grid mix is the mix of fossil fuel and renewable energy that is used at a location at any given moment or day. The carbon emissions display metric 936 and carbon emissions video metric 940 also includes supply chain emissions, which may incorporate an analysis of a domain’s ad. txtfile to discern the ad chains of ad tech and vendors being used to deliver a single ad. The carbon emissions display metric 936 and carbon emissions video metric 940 is further normalized for factors such as time, file weight, location and device so as to compensate for differences between domains based on their ad technology setups. As energy usage for the advertising of a domain increases, the carbon emissions for said domain increase, and hence the carbon emissions display metric 936 and carbon emissions video metric 940 increase accordingly. As the carbon emissions display metric 936 and carbon emissions video metric 940 for a domain increase, the ethical media index score 900 for said domain decreases. More specifically, in the current embodiment, there is an inversely proportional relationship between the carbon emissions display metric 936 and the ethical media index score 900. In addition, in the current embodiment, there is an inversely proportional relationship between the carbon emissions video metric 940 and the ethical media index score 900.

[0060] The invalid traffic metric 944 measures the amount of internet traffic that is generated by bots. Bots may visit websites and mimic human behavior for malicious purposes. However, regardless of whether a human or a bot visits a website, activity is generated, and hence there is a consumption of energy and a generation of greenhouse gas emissions. To that end, the amount of internet traffic generated by bots is considered invalid traffic, as it is traffic that receives advertising impressions, however is not delivered or served to users. As the amount of invalid traffic increases, the invalid traffic metric 944 increases, and the ethical media index score 900 for a domain decreases. More specifically, in the current embodiment, there is an inversely proportional relationship between the invalid traffic metric 944 and the ethical media index score 900.

[0061] In alternate embodiments, a viewability metric may also be included as part of advertising score 908. A viewability metric measures the average % of adverts on a website that are visible to a user of that website for a minimum of one second. Advertisements that are served and are not viewable have no utility and therefore represent wastage and unnecessary energy usage. For example, if an advertisement is served at the bottom of a web page of content, and the user does not scroll down to said bottom of the webpage, then the advertisement is not viewed by the user, and instead is hidden. As such, as the percentage of the viewability metric increases, theethical media index score 900 increases. More specifically, in this alternate embodiment, there is a proportional relationship between the viewability metric and the ethical media index score 900.

[0062] In yet another embodiment, a screen energy consumption metric (not shown) may also be included as part of advertising score 908. Webpages or domains may receive data as encoded data per page in megabytes and advertisement encoded data per page in megabytes. The larger the data transfer in megabytes, the higher the screen energy consumption. As part of the screen energy consumption metric, the amount of megabytes for encoded data per page and advertisement encoded data per page is received and converted to an index using a logistical curve. Specifically, the higher the score for a screen energy consumption metric, the lower the data transfer. More specifically, in this alternate embodiment, there is a proportional relationship between the screen energy consumption metric and the ethical media index score 900.

[0063] In another embodiment, the advertisement density metric (not shown) may also contribute to advertising score 908. The advertisement density metric measures the advertisement clutter on a page, and therefore measures the efficacy of the advertising. The higher the advertisement clutter on a page, the less effective the advertisement is. A domain or website may be scrapped to determine the number of advertisements that load within a predetermined time period. In the current embodiment, a scape of a website or domain may return the number of advertisements that loaded within a minute. The number of advertisements may then be converted into an indexed value using a logistic curve. As such, a higher score means there is less advertisement clutter on the website or domain. Specifically, the advertisement density metric is directly proportional to ethical media index score 900.

[0064] A person skilled in the art will recognize that there are other additional metrics that may be used to measure the environmental impact and energy usage of the domain, and that any number of the above-mentioned metrics or other metrics may be included in the advertising score 908.

[0065] Returning to FIG. 1 , in the current embodiment, as instructed by advertising scoring module 124, processor 112 may query or request the advertising data of at least one domain from advertising databases 152 via communications interface 108 over WAN 140. In the current embodiment, the request or query may be made to a single advertising database 152 that is externalto ethical media index scoring engine 104. However, it will occur to a person skilled in the art that the request or query may be made to more than one database, and that said database or databases may be either external to ethical media index scoring engine 104, internal within ethical media index scoring engine 104, or a hybrid of both. A person skilled in the art will also recognize that any query to advertising databases 152 external to ethical media index scoring engine 104 may be via communications interface 108 and WAN 140, and that any query to corporate databases 152 that may be internal to ethical media index scoring engine 104 may be within memory 116.

[0066] Upon receiving the requested advertising data from advertising database 152 via WAN 140 and communications interface 108, processor 112 may then determine if there are any missing or incomplete metrics or data for each domain. If there are missing or incomplete metrics, then processor 112 may refer to schema 136 to determine next actions to compensate for the missing or incomplete metrics. This will be further discussed below.

[0067] Once processor 112 has compensated for the missing or incomplete metrics, each metric may be further modified based on schema 136. Specifically, each metric may be normalized and then weighted based on information provided from schema 136. This will also be further discussed below.

[0068] Advertising scoring module 124 may then provide instructions to processor 112 to merge the relevant metrics to create advertising score 908. In the current embodiment, advertising scoring module 124 provides instructions to processor 112 to merge the carbon emissions display metric 936, the carbon emissions video metric 940 and the invalid traffic metric 944 to create advertising score 908. In alternate embodiments, advertising scoring module 124 may further provide instructions to processor 112 to merge the viewability metric as part of the creation of the advertising score 908. A person skilled in the art will recognize that any number of the abovementioned metrics or other metrics related to the company owning the domain may be merged to create advertising score 908.

[0069] In at least some embodiments, memory 116 stores content scoring module 128. Similar to the corporate scoring module 120 and the advertising scoring module 124, the execution of content scoring module 128 by processor 112 allows for the modification and normalization of content data received from content databases 156, and for the compensation of any missing orincomplete metrics or data points from the content data received from content databases 156. The content scoring module 128 also provides instructions to processor 112 to create the content score 912 for a specified domain.

[0070] The content score 912 is a measurement of the type of content that a website / domain produces and whether the content being produced is produced in a responsible and accurate manner. As an example, an advertiser wishing to buy ethical media would not want to be on a website that is publishing climate misinformation. In addition, as advertising funds the websites, the content score 912 also reflects the fact that the content a website produces may influence the behaviours and lifestyle choices of its readers.

[0071] Referring to FIG. 9 again, in the current embodiment, the content score 912 may include at least an Interactive Advertising Bureau (IAB) category metric 948, a Sustainability Development Goals (SDG) alignment metric 952, and a media quality metric 956.

[0072] The IAB category metric 948 measures whether the content of a domain falls under a specific category under the taxonomy that is defined by the IAB, and whether said category is considered positive, neutral or negative based on the categories’ alignment with the United Nations SDG. A person skilled in the art will recognize that the IAB has standard classifications that publishers and brands use to categorize web content and to improve targeting. The categories are provided in two tiers, Tier 1 which encompasses broader categories, such as IAB1 Arts & Entertainment, and Tier 2 which encompasses more specific categories, such as IAB 1-1 Books & Literature and IBA1-2 Celebrity Fan / Gossip. A person skilled in the art will recognize that IAB categories may change and evolve over time as new categories are developed.

[0073] The United Nations SDG are goals that are outlined by the United Nations as a call to action with the goal of peace and prosperity for people and the planet, now and into the future. A person skilled in the art will recognize that United Nations SDGs may change over time. Currently, there are seventeen specific United Nations SDGs, covering a range of subjects including, as an example, (i) Climate Action, to take urgent action to combat climate change and its impacts; (ii) Reduce Inequalities, to reduce inequality within and among countries; and (iii) Good Health and Wellbeing, to ensure healthy lives and promote well-being for all at all ages.

[0074] Each IAB category may be deemed to be either positive, neutral or negative based on its alignment to with the United Nations SDG. As an example, an IAB category of “diesel” for automotive may be considered negative, as it does not align with keeping the environment clean. Similarly, the IAB category of “electric vehicles” may be considered positive, as it does align with keeping the environment clean. Alternatively, an IAB category of “convertibles” may be considered neutral as it does not align with any United Nations SDG. The mapping of IAB categories to United Nations SDG may reside in memory 116, and may further be updated on a regular basis to ensure that any changes to the United Nations SDG or the IAB categories are included.

[0075] In the current embodiment, a domain’s IAB categories may be returned by querying content databases 156. A domain may have more than one IAB category associated with the domain’s content. Upon receiving the specific number of IAB categories, the IAB categories are mapped against the United Nations SDGs. Specifically, a score of “+1”, “0” or “-1” is assigned to each IAB category for the domain. A “+1” is for a positive IAB category when mapped with the United Nations SDG. A “0” is for a neutral IAB category when mapped with the United Nations SDG. A “-1” is for a negative IAB category when mapped with the United Nations SDG. The total score is then summed and normalized to provide the IAB category metric 948. For example, a domain with three IAB categories associated with the domains’ content may have a summed / aggr egates score of “-3”. This may then be normalized. In the current embodiment, if the scale of aggregated scores is between “-5” and “5”, and the aggregated scores is normalized in a linear fashion to a range between 0 to 100, then an aggregated score of “-5” would be “0”, an aggregated score of “5” would be “100”, and the example aggregated score of “-3” would be “20”. In the current embodiment, the more IAB categories that the domain relates to that are aligned with the United Nations SDG goals, the IAB category metric 948 increases, and the ethical media index score 900 also increase. Specifically, there is a proportional relationship between the IAB category metric 948 and the ethical media index score 900.

[0076] In an alternate embodiment, a domain’s IAB categories may be returned by scraping a domain’s content and analyzing the content that is scraped, a domain’s IAB categories may be determined. This may be done through various means, including determine whether certain keywords are present and / or by using sentiment analysis. Sentiment analysis of the contentwill provide additional context as to whether the content is considered to be positive, neutral or negative.

[0077] The SDG Alignment metric 952 determines and quantifies where if the IAB category metric 948 is considered to be neutral or positive, whether there are other additional United Nation SDGs that the domain content may align with. For each additional United Nation SDG that the domain content aligns to, an additional score of “+1” is given. The total score is then summed to provide the SDG alignment metric 952. If the IAB category metric 948 is considered to be negative, then the SDG alignment metric 952 is considered to be “0”. In the current embodiment, the more United Nation SDGs that a domain aligns to, the higher the SDG alignment metric 952, and the higher the ethical media index score 900. Specifically, an SDG alignment metric 952 is directly proportional to the ethical media index score 900.

[0078] In an alternate embodiment, the SDG Alignment metric 952 may also be determined by scraping the domain content. More specifically, the domain content or website content may be scraped or crawled for specific keywords. The tool for scraping may include the use of large language models (LLMs) to capture variations of keywords and text. Certain key subdomains or websites will be included within the scrape, and may further include additional weight. For example, the main home page, the “about us” section, the site map or the navigational links will be focussed upon for scraping. Keywords that are searched for align with the United Nation SDGs, and certain keywords may have a higher weight than others with regards to its importance with regards to the United Nation SDGs. The availability or hit of a keyword on a domain or a website will be weighted and then may affect the score of the SDG Alignment metric 952.

[0079] The media quality score 956 measures the quality of the domain’s content and whether the domain’s content spreads misinformation and disinformation. The media quality score 956 may include examining (i) bias, whether a domain’s content is left wing or right wing; and (ii) factual reporting, whether a domain’s content is factual or not. A domain’s media quality score 956 may be either “low”, “medium” or “high”. In the current embodiment, a “low” media quality score 956 will lower the ethical media index score 900, a “medium” media quality score 956 will not affect the ethical media index score 900, and a “high” media quality score 956 will increasethe ethical media index score 900. Specifically, the media quality score 956 is directly proportional to the ethical media index score 900.

[0080] A person skilled in the art will recognize that there are other additional metrics that may be used to measure the quality of the content of a domain and whether the content is considered to be ethical or sustainable, and that any number of the above-mentioned metrics or other metrics may be included in the content score 912.

[0081] Returning to FIG. 1, in the current embodiment, as instructed by content scoring module 128, processor 112 may query or request the content data of at least one domain from content databases 156 via communications interface 108 over WAN 140. In the current embodiment, the request or query may be made to a single content database 156 that is external to ethical media index scoring engine 104. However, it will occur to a person skilled in the art that the request or query may be made to more than one database, and that said database or databases may be either external to ethical media index scoring engine 104, internal within ethical media index scoring engine 104 or a hybrid of both. A person skilled in the art will also recognize that any query to content databases 156 external to ethical media index scoring engine 104 may be via communications interface 108 and WAN 140, and that any query to content databases 156 that may be internal to ethical media index scoring engine 104 may be within memory 116.

[0082] Upon receiving the requested content data from content database 156 via WAN 140 and communications interface 108, processor 112 may then determine if there are any missing or incomplete metrics for each domain. If there are missing or incomplete metrics, then processor 112 may refer to schema 136 to determine next actions to compensate for missing or incomplete metrics. This will be further discussed below.

[0083] Once processor 112 has compensated for missing or incomplete metrics, each metric may be further modified based on schema 136. Specifically, content scoring module 128 may instruct processor to modify the data based on mappings and an analysis of the content, an example of which has been provided above. The metrics may then be normalized and weighted based on information provided from schema 136. This will also be further discussed below.

[0084] Content scoring module 128 may then provide instructions to processor 112 to merge the relevant metrics to create content score 912. In the current embodiment, content scoring module 128 provides instructions to processor 112 to merge the I AB category metric 948, the SDG alignment metric 952 and the media quality metric 956. A person skilled in the art will recognize that any number of the abovementioned metrics or other metrics related to the company owning the domain may be merged to create content score 912.

[0085] In at least some embodiments, memory 116 stores data 132. Data 132 may include historical data for domains. Specifically, data 132 may include a log of metrics for domains. Additionally, data 132 may include a historical log of corporate score 904, advertising score 908, content score 912 and ethical media index score 900 for domains. Historical logs of scores allow for analyses to be run to determine a domain’s ethicality over time, including a determination of whether there is an improvement of ethicality over time for a domain.

[0086] Data 132 may also include other databases, such as the previously mentioned mapping of IAB categories to United Nations SDG alignment, or a list of information related to each domain. In the current embodiment, data 132 may also include descriptions of each domain, and whether a domain is related to a user’s advertisement campaign.

[0087] In at least some embodiments, memory 116 stores schema 136. An example of schema 136 is depicted in FIG. 8. Schema 136 provides different processes and different variables for the modification of the data received from corporate databases 148, advertising databases 152, and content databases 156. More specifically, each record of schema 136 provides a blueprint of each metric within each scoring category.

[0088] In the current embodiment, as previously indicated, there are at least three scoring categories as is indicated in group name 808, the corporate score 904, the advertising score 908 and the content score 912. In addition, in the current embodiment, as has been described above, the metrics are provided in metric name 804 and may include environment metric 916, social metric 920, governance metric 924, employee metric 928, diversity metric 932, carbon emissions display metric 936, carbon emissions video metric 940, invalid traffic metric 944, IAB category metric 948, SDG alignment metric 952, and media quality metric 956. In an alternate embodiment, the visibility metric may also be included. More specifically, the metric names 804 associated withthe environment metric 916, social metric 920, governance metric 924, employee metric 928 and diversity metric 932 are associated with the group name 808 of the corporate score 904. The metric names 804 associated with the carbon emissions display metric 936, carbon emissions video metric 940 and invalid traffic metric 944 are associated with the group name 808 of the advertising score 908. The metric names 804 associated with the IAB category metric 948, SDG alignment metric 952 and media quality metric 956 are associated with the group name 808 of the content score 912. A person skilled in the art will recognize the different metric names 804 and different group names 808. In addition, a person skilled in the art will also recognize the different potential combinations between metrics names 804 and group names 808.

[0089] Schema 136 may include the metric type 812. Metric type 812 denotes the type of data that metric name 804 is. In the current embodiment, metric type 812 may either be “numerical” or “category”. A “numerical” metric type 812 indicates that metric name 804 is a number or integer. A “category” metric type 812 indicates that metric name 804 is a predetermined list of characters, or a string, or alternatively, an array of characters or strings. An example of this is the aforementioned media quality metric 956, in which the available list of strings that the metric may be are “low”, “medium” and “high”. A person skilled in the art will also recognize the different data types that may be used within metric type 812. In addition, a person skilled in the art will recognize the different potential combinations between metric names 804 and metric types 812.

[0090] Schema 136 may also include weight 816. Weight 816 provides the weight or scale of metric name 804. Specifically, ethical media index score 900 includes each metric name 804 as a weighted sum. More specifically, each metric name 804 is multiplied by the weight before being merged together to create ethical media index score 900. As such, the sum of all the weights will equate to one (this is not shown as FIG.8 depicts only a portion of schema 136). Weight 816 may also be represented as a percentage where the sum of all weights for each metric number 804 is equal to 100 percent. In the current embodiment, the IAB category metric 948 has a weight of 0.045 or 4.5%. As such, data for the IAB category metric 948 is multiplied by the weight of 0.045 or 4.5% to be incorporated into both the content score 912, as is provided by group name 808, and the ethical media index score 900. More specifically, the processor 112 will be able to determine the weight of each metric by referencing weight 816 of schema 136. As another example in thecurrent embodiment, the carbon emissions video metric 940 has a weight of 0.065 or 6.5%. As such, data for the carbon emissions video metric 940 is multiplied by the weight of 0.065 or 6.5% to be incorporated into both the advertising score 908, as is provided by group name 808, and the ethical media index score 900.

[0091] Schema 136 may also include null replace 820. Null replace 820 provides instructions to processor 112 on how to compensate when data is missing or incomplete for metric name 804. Null replace 820 may be a value, in which if data is missing or incomplete the value is to be inserted in place of the missing or incomplete data for metric name 804. In addition, null replace 820 may be a function, in which if data is missing or incomplete, the function is used to calculate the missing or incomplete value. In the current embodiment, when processor 112 determines there is missing or incomplete data in the IAB category metric 948, processor 112 may compensate for the missing or incomplete data in the IAB category metric 948 by replacing the missing or incomplete data with “0”. Similarly, when processor 112 determines there is missing or incomplete data in the carbon emissions video metric 940, processor 112 may compensate for the missing or incomplete data in the carbon emissions video metric 940 by replacing the missing or incomplete data with “50”. In addition, when processor 112 determines there is missing or incomplete data in the social metric 920, denoted as “esg community” under metric name 804, processor 112 may compensate for the missing or incomplete data in the social metric 920 by replacing the missing or incomplete data by using the mean function, and specifically using the mean value of all social metric 920 data over a predetermined time frame. In the current embodiment, the predetermined time frame is quarterly. However, a person skilled in the art will recognize that the predetermined time frame may be over any amount of time, or may be based in real time. Other functions may be contemplated, including, but not limited to, an exponential function or a linear function. Multiple functions may also be contemplated, such as the modification of the data over several steps. In alternative embodiments, null value 820 may be a coding module including several functions or instructions for processor 112. A person skilled in the art will recognize that the data for each metric name 804 is specific and unique to said metric name 804 and as such, there are different values, functions, modules or instructions available for each null replace 820 for each respective metric name 804. A person skilled in the art will also recognize the different potential functions that can be used for each metric name 804.

[0092] Schema 136 may also include direction 824. Direction 824 indicates whether the data of metric name 804 is directly proportional or inversely proportional to ethical media index score 900. Specifically, if direction 824 has a value of “low” then the data from metric name 804 is directly proportional. If direction 824 has a value of “high” then the data from metric name 804 is inversely proportional. In the current embodiment, the IAB category metric 948 has a direction 824 of “high”, which indicates that the IAB category metric 948 is directly proportional to the ethical media index score 900. Similarly, the carbon emissions video metric 940 has a direction 824 of “low”, which indicates that the carbon emissions video metric 940 is inversely proportional to the ethical media index score 900. A person skilled in the art will recognize the different potential combinations and configurations of metric name 804 and direction 824.

[0093] Schema 136 may also include bucketing type 828. Bucketing type 828 provides the instructions to be used by processor 112 to normalize metric name 804. In the current embodiment, bucketing type 828 may include “logistic”, “exponential”, “normalization” or “index”. Each bucketing type 828 provides different instructions to processor 112 on how to modify data for a specific metric name 804. The “logistic” bucketing type 828 places the data or value of metric name 804 on a logistic curve or S-curve. The “exponential” bucketing type 828 places the data or value of metric name 804 on an exponential line. The “normalization” bucketing type 828 places the data or value of metric name 804 on a linear line or linear scale. The “index” bucketing type 828 indicates that the data or value of metric name 804 does not need to be modified. Schema 136 may also include bucketing settings 832. The function that is called by bucketing type 828 uses the variables that are provided in bucketing settings 832. In the current embodiment, with respect to the metric name 804 of IAB category metric 948, the bucketing type 828 is “normalization”, and the bucketing settings 832 is “10, -10”. In referencing bucketing type 828 and bucketing settings 832, processor 112 is hence instructed to take data or values of IAB category metric 948 and convert them from a linear scale of 10 to -10 to a linear scale of 100 to 0. Furthermore in the current embodiment, with respect to the metric name 804 of carbon emissions video metric 940, the bucketing type 828 is “logistic”, and the bucketing settings 832 is “100, 0.01, 600”. In referencing bucketing type 828 and bucketing settings 832, processor 112 is hence instructed to take the data or values of carbon emissions video metric 940 and place the value on a logistic curve with a maximum threshold for the curve of 100, a steepness of curve of 0.01, and a midpoint of 600. A person skilled in the art will recognize that the bucketing type 828 is not limited to theprovided options, but may be of any function or modification of data. Furthermore, a person skilled in the art will also recognize the different potential configurations and combinations of bucketing type 828, bucketing settings 832 and metric name 804.

[0094] The inclusion of schema 136 in memory 116 allows corporate scoring module 120, advertising scoring module 124 and content scoring module 128 to improve the processing speed of the data by processor 112. Specifically, by having processor 112 refer to schema 136, the number of loops and definitions are reduced, improving the processing speed. Furthermore, the addition of schema 136 in memory 116 allows for the addition of new metrics without the need for custom modules or custom coding.

[0095] In other embodiments, memory 116 may also include different schemas 136 (also referred to as meta-tables 136) for different forms of media or channels. For example, an ethical media score may also be provided to an app, tv channels, YouTube channels, and / or digital out- of-home media, including, but not limited to billboards, and / or posters. A schema 136 for a tv channel may be stored in memory 116 and provide instructions for processor 112 for the processing of data related to tv channels. Similarly, a schema 136 for an app may provide instructions for processor 112 for the processing of data related to apps. By having separate schemas 136 for different media sources or media types, the function or logic applied for the calculation of the ethical media score, corporate score 904, advertising score 908 and content score 912 may differ between said different media sources, allowing for added accuracy based on the media type. A person skilled in the art will recognize that different media types and / or media channels and the configurations of different schemas 136 for said different media types and / or media channels are contemplated, and that the different media types and / or media channels are not limited to the ones provided in the example above.

[0096] Ethical media index scoring engine 104 further includes communications interface 108. Communications interface 108 allows for processor 112 to communicate with WAN 140. Communications interface 108 includes suitable hardware (e.g. transmitters, receivers, network interface controllers and the like) allowing ethical media index scoring engine 104 to communicate with other components in system 100, such as client terminal 144 and databases 148, 152 and 156. The specific components of communications interface 108 may be selected based on the type ofnetwork or other links that ethical media index scoring engine 104 may be required to communicate over.

[0097] Ethical media index scoring engine 104 may also include input devices that connect to processor 112, such as a keyboard and mouse, as well as output devices, such as a display. Alternatively, or in addition, the input and output devices can be connected to processor 112 via communications interface 108 via another computer device. In other words, input and output devices can be local to ethical media index scoring engine 104 or remote. In the present embodiment, a display may output or provide the example graphical user interfaces in FIGS. 4 to 7. This will be further discussed below.

[0098] WAN 140 is an example implementation of the connection between components in system 100, and a person skilled in the art will recognize that WAN 140 is not particularly limited in its configuration. WAN 140 may be any form of network, including a local area network (LAN), or the Internet, and may be accessed by computers, mobile devices or the components of system 100. Computers, such as ethical media index scoring engine 104 and client terminal 144 can operate in a networked environment using logical connections to one or more remote computers or other devices, such as a server, a router, a network personal computer, a personal computer, a peer device or other common network node, a wireless telephone or wireless personal digital assistant. In the current embodiment, WAN 140 may be implemented over the Internet. The standards or protocols used for the network may include any form of transmission, such as Transmission Control Protocol / Internet Protocol (TCP / IP), User Datagram Protocol / Internet Protocol (UDP / IP), Hyper Text Markup Language (HTML) and Hyper Text Transfer Protocol (HTTP). In addition, any desired levels and types of security and encryption protocols are contemplated and can be implemented over WAN 140. A person skilled in the art will recognize the different potential network types and different potential network configurations that may be used, along with the different standards and protocols of transmission within the network, and the different forms of security and encryption protocols available.

[0099] System 100 may include client terminal 144. Client terminal 144 can be a computer device such as, but not limited to, a desktop computer, a laptop computer, another server, a kiosk,a cell phone, a tablet, a mobile device, a monitor or other suitable device. A person skilled in the art will also appreciate that other, different configurations of client terminal 144 are contemplated.

[0100] Client terminal 144 may include input devices and output devices. In the present embodiment, client terminal 144 may include a display that outputs or provides the example graphical user interfaces in FIGS. 4 to 7.

[0101] Referring to FIG. 4, an example graphical user interface 400 (also referred to herein as screen 400) is provided showcasing a list of domains 444 and their associated ethical media index score 900, corporate score 904, advertising score 908, and content score 912. The list of domains 444 may be ranked based on ethical media index score 900 at column 416. The confidence level of the data being provided to produce the ethical media index score 900 may be provided at column 420. The specific domain related to the ethical media index score 900 and other scores is at column 424. The ethical media index score is at 428 and includes a colour indicator as to whether the ethical media index score 900 is considered to be high, medium or low. In addition, the corporate score 904, advertising score 908 and corporate score 912 may be provided at columns 440, 432 and 436 respectively, each with their own colour indicators for each domain. Block 412 also provides the total number of sites or domains that have been evaluated and have an ethical media index score 900. When interacting with the graphical user interface 400, a user may select a domain within list 444 to provide additional details. After selecting or highlighting a domain, block 404 may display the current ethical media index rank, and block 408 may display the current ethical media index score 900. A person skilled in the art will recognize the different layouts for the columns in list 444, and that the presentation of information in the aforementioned columns is not limited to columns, but may be presented in any format. A person skilled in the art will further recognize the different potential layouts and configurations for displaying the information and data provided in graphical user interface 400.

[0102] Referring to FIG. 5, an example graphical user interface 500 is provided that provides additional information about a domain that is selected. Similar to graphical user interface 400, graphical user interface provides a list of domains 444, however the number of columns provided may be reduced. In the current embodiment, columns 416, 420424 and 428 are provided showcasing the ethical media index rank, the confidence level, the domains and the ethical mediaindex score 900 respectively. In addition, blocks 404, 408 and 412 may also be provided, presenting the ethical media index rank of the selected domain, the current ethical media index score 900 of the selected domain and the total number of sires or domains that have been evaluated. Description 512 provides general information about the selected domain. The description 512 may be previously drafted and placed within a database to be pulled and displayed on graphical user interface 500. In alternate embodiments, description 512 may be generated by artificial intelligence engines such as ChatGTP. Interactive chart 504 provides a bar chart indicating the corporate score 904, advertising score 908 and content score 912. In addition, chart 504 further provides bars for the average corporate score, average advertising score and average content score across all evaluated domains. Graphical user interface 500 may also include chart 508. Chart 508 provides the ethical media index score 900 as a bar and provides a comparison to other sources of data, specifically the average ethical media index score 900 for other lists and sources, such as the top 500 sites by audience as is provided by Comscore or the member sites of the Association of Online Publishers (AOP). A person skilled in the art will recognize the potential layouts and configurations that may be used for the elements on graphical user interface 500.

[0103] Referring to FIG. 6, an example graphical user interface 600 is provided where data regarding a subset of domains is provided to the user. More specifically, a user may indicate via the graphical user interface specific domains that the user wishes to monitor, or specific domains that are part of the user’s advertising campaign. The information for said campaigns may then be retrieved via API calls from external databases or external sources and presented as chart 616. More specifically, chart 616 provides a summation or merged total of statistics based in advertising, including at least, but not limited to the number of impressions, the green house gases produced, the number of clicks the ad gets, the click through rate (CTR), the view through rate (VTR) and viewability of the ad. Graphical user interface 600 may also include a carbon impact chart 604, which provides the industry average carbon output, and the average carbon output of all the evaluated domains, and the carbon output for the user’s subset of domains as part of the user’s advertising campaign. A comparison of the average ethical media index score 900 of the subset of domains of the user’s campaign and the average ethical media index score 900 for other lists and sources is provided at chart 608. Chart 608 is similar to the previously described chart 508, however the average ethical media index score 900 for the campaign is provided in chart 608 rather than the ethical media index score 900 for a single selected domain. Graphical user interfacefurther includes chart 612, where the top performing publishers from the user’s advertising campaign is provided with respect to viewability, CTR and VTR. A person skilled in the art will recognize the different potential statistics that may be used in graphical user interface 600 in relation to an advertising campaign. A person skilled in the art will further recognize the potential layouts and configurations for data pertaining to a user’s advertising campaign and how it relates to the ethical media index score 900.

[0104] In alternate embodiments, graphical user interfaces may also include other data from advertising campaigns, including, but not limited to, data such as the number of ads delivered and the websites that the ads were delivered on, the performance of the ads (i.e. the number of clicks on the ad), the different creative messages that were in the ads, and what media owners were used to deliver the ads. The aforementioned data associated with the advertising campaign, and also the data associated with the advertising campaign from example graphical user interface 600 may then be processed in conjunction with ethical media index score 900 to provide insight to inform how future campaigns may be planned and optimized. As an example, the future planning and optimization of advertising campaigns may include either including or excluding different websites on a combination of ethical media index scores 900 and other metrics / measurements (i.e. environment metric 916, social metric 920, etc.). By providing the ethical media index scores 900 associated with a user’s advertising campaign, decisions may be made based on a standardized set of values that may be compared to one another on a single scale.

[0105] In yet another alternative embodiment, artificial intelligence models may be used to evaluate the ethical media index scores 900 and the metrics that are part of the ethical media index scores 900, where processor 112 is able to provide to a graphical user interface written explanations regarding the metrics and ethical media index scores 900, and also provide to a graphical user interface recommendations for future actions / changes, such as the removal or the addition of domains or businesses to the advertising campaign.

[0106] Referring to FIG. 7, an example graphical user interface 700 is provided where data is provided regarding the advertising statistics of a selected domain and also the domain’s ethical media index score, allowing a user to determine a domain’s viability for advertising from both its monetary or advertising performance and its ethical media index score 900. An advantage ofgraphical user interface 700 is that the graphical user interface 700 allows a user to select which websites to incorporate into advertising campaigns based on a favorable ethical media index score 900, or which websites to incorporate into advertising campaigns to improve performance targets. Similar to graphical user interface 500, a list of domains 444 is provided, however the number of columns provided is reduced. In the current embodiment, columns 416, 424 and 428 are provided showcasing the ethical media index rank, the domains and the ethical media index score 900 respectively. In addition, a description of the domain is provided as description 512. From an advertising statistics standpoint, graphical user interface 700 provides the information for the selected domain at table 708. From an ethicality stand point, graphical user interface 700 provides the United Nations SDGs that the domain aligns to at list 704. This provides an insight into the SDG alignment metric 952. In addition, graphical user interface 700 includes chart 716 which presents the domain’s ethical media index score 900, corporate score 904, advertising score 908 and content score 912. A person skilled in the art will recognize the potential advertising statistics associated with the domain that can be presented in graphical user interface. A person skilled in the art will further recognize the potential layouts and configurations for data pertaining to the advertising statistics, the ethical media index score 900, the corporate score 904, the advertising score 908 and content score 912.

[0107] Referring to FIG. 2, method 200-1 depicts an example method for creating either corporate score 904, advertising score 908, or content score 912. Method 200-1 may be performed by processor 112 when being instructed by corporate scoring module 120, advertising scoring module 124 or content scoring module 128. Specifically, corporate scoring module 120 may instruct processor 112 to generally follow method 200-1 to create or update corporate score 904. Similarly, advertising scoring module 124 may instruct processor 112 to generally follow method 200-1 to create or update advertising score 908. Similarly, content scoring module 128 may instruct processor 112 to generally follow method 200-1 to create or update content score 912.

[0108] Step 205 includes processor 112 requesting or querying data for a metric for a specified domain. The request or query is sent from processor 112 to the appropriate database. In the current embodiment, the request or query is sent from processor 112 via communications interface 108 and WAN 140 to external databases 148, 152 and 156 depending on the scoring module and metric type 812. The request or query may be in any form depending on the format ordatabase type of databases 148, 152 and 156. For example, the request or query may be an Application Programming Interface (API) call, or may be a query in Structured Query Language (SQL). A person skilled in the art will recognize the different potential request or query types that may be used. In a preferred embodiment, step 205 includes processor 112 requesting or querying data for a single specified domain. The data requested may be a single metric, or may be several metrics from the appropriate database based on the metric name 804 and which group name 808 the metric name 804 is associated with. In an alternate embodiment, step 205 may include processor 112 requesting or querying data for a single metric over multiple domains, or data for multiple metrics over multiple domains. A person skilled in the art will recognize the potential configurations for requesting or querying data and metrics for domains.

[0109] Step 210 includes processor 112 receiving the data that was requested or queried in step 205 from the appropriate database. In the current embodiment, the data is received by processor 112 via communications interface 108 and WAN 140 from external databases 148, 152 and 156.

[0110] In a preferred embodiment, step 215 includes processor 112 for determining if there is any missing or incomplete data from the data that was received in step 210. In the preferred embodiment, processor 112 reviews the data or metrics received from the applicable database and determines if there is any data missing, incomplete or whether there is any data that is unavailable. If there is no data missing or incomplete, processor 112 may proceed to method 200-2 once all data or metrics has been received for a specified domain. If there is data missing or incomplete, processor 112 may, in a preferred embodiment, compensate for missing or incomplete values based on schema 136. This is depicted at step 220. Step 220 includes processor 112 referring to schema 136 to determine how to compensate for missing or incomplete values. More specifically, as previously mentioned, schema 136 provides either a value or a function for processor 112 to replace the missing or incomplete data with for each metric.

[0111] Step 225 includes processor 112 modifying the confidence score value. A confidence score value may be provided in conjunction with each ethical media index score 900 to provide an indication to the user as to the accuracy of said ethical media index score 900 for a specified domain. Specifically, a confidence score value decreases each time there is missing orincomplete data and when processor 112 replaces the missing or incomplete data with a value or based on a function from schema 136. The confidence score value decreases based on the weight 816 of the missing or incomplete data of the specific metric name 804 in schema 136. For example, referring to FIG. 8, a domain which has no missing or incomplete data has a confidence score value of 100%. However, a domain which has missing or incomplete data for the IAB category metric 948 will have a confidence score value of 95.5% for the ethical media index score 900. This may be calculated by the confidence score value of 100% subtracting 4.5%, which is determined by IAB category metric 948 metric name 804 having an associated weight 816 of 4.5% in schema 136. Continuing on with the example, if the domain has missing or incomplete data for both the IAB category metric 948 and the carbon emissions video metric 940, the ethical media index score 900 will have a confidence score value of 89%, which is calculated by the confidence score value of 100% subtracting 4.5% for the weight 816 of the IAB category metric 948, and also 6.5% for the weight 816 of the carbon emissions video metric 940 as is provided in schema 136. Returning to FIG. 2, in the current embodiment for step 225, processor 112 refers to schema 136 to determine the weight 816 of the specific metric name 804 that is missing or incomplete data in order to calculate the confidence score value for a domain.

[0112] Referring to FIG. 3, method 200-2 is a continuation of method 200-1. Step 230 includes processor 112 modifying the data based on schema 136. Modifying the data based on schema 136 includes two substeps: i) processor 112 may refer to schema 136 for bucketing type 832 and bucketing settings 832 to modify the specified metric name 804; and ii) processor 112 may also further modify the data based on the weight 816 of the specified metric name 804. Both of these substeps have been previously described above. For example, in the current embodiment, the data for carbon emission video metric 940 may be modified based on a logistic curve with the parameters of 100, 0.01 and 600 as is provided in schema 136 under bucketing type 828 and bucketing settings 832. Once the data for the carbon emission video metric 940 has been modified based on the logistic curve, the data is further modified based on weight 816. More specifically, the data is further multiplied by the weight 816 of 0.065. This modified data represents the carbon emission video metric 940.

[0113] Once all the metrics for a domain have been modified, the corporate score 904, advertising score 908 and content score 912 may be calculated by merging the respective metricsunder each respective group name 808 and normalizing it based on the weight 816 of all the metrics combined for said group name 808. The ethical media index score 900 may also be calculated either by adding all the metrics for specified domain after having been modified (as the weights of all the metrics add up to “1” or “100%”), or merging the corporate score 904, advertising score 908 and content score 912 together and normalizing based on the weight 816 of all the metrics for the group name 808. This is depicted as step 235.

[0114] At step 240, the ethical media index score 900 is displayed in graphical user interfaces for a user to review. At step 245, the corporate score 904, advertising score 908, content score 912 and ethical media index score 900 is logged as historical data in data 132. The logging of corporate score 904, advertising score 908, content score 912 and ethical media index score 900 allow for the analysis of each of these metrics and / or scores over time, which may also be provided on a graphical user interface. Analysis may lead to providing reports to be displayed on the graphical user interface with the overall trends and distribution of scores within the ethical media index 900, the percentage of advertiser spend going to web domains in different ethical media index 900 quartiles, the unique user growth of a representative group of ethical media web domains, and / or consumer attitudes.

[0115] At step 250, processor 112 determines if the scores are due for an update. Scores may be updated at predetermined intervals, such as quarterly or annually. In alternate embodiments, scores may be updated manually based on a request from a user or administrator. Furthermore, in alternate embodiments, scores may be updated based on a trigger, such as a scraper determining a certain percentage of change in content on a domain. A person skilled in the art will recognize the different potential intervals, reasons or triggers for scores to be updated. If scores are to be updated, method 200-1 is performed by processor 112. If scores are not to be updated, processor 112 waits a predetermined interval or waits for the next trigger at step 255.

[0116] System 100 and methods 200-1 and 200-2 may be used by customers to measure how ethical and sustainable their digital advertising campaign has been. For example, an advertiser may provide data to system 100 referring to the volume of adverts bought across different web domains for a specific advertising campaign. System 100 via methods 200-1 and 200-2 would provide data back indicating the ethical media index scores 900 for each of the domains in thecampaign. In addition, further insight is provided from the ethical media index scores 900 that can be used for future media planning decisions.

[0117] In alternate embodiments, system 100 and methods 200-1 and 200-2 may also be used by companies to deliver both improved marketing performance and improved ESG metrics to their customers. This will improve the overall reputation and standing of the company owning the website and / or domain.

[0118] Alternatively, system 100 and methods 200-1 and 200-2 may also be used by companies to measure their digital marketing expenditure against their corporate ESG goals. This allows a company to measure their effectiveness and return based on their expenditure. This is equivalent to the determination on a return on investment based on corporate ESG goals. A company can then determine whether funds are optimally deployed to reach their corporate ESG goals. In another example, companies may also score the media or domain that they have purchased, and evaluate its progress over time based on its expenditure. In yet another embodiment, companies may also quantify the percentage of their marketing expenditure which funds content that is aligned to their specific sustainability goals.

[0119] In yet another embodiment, system 100 and methods 200-1 and 200-2 may be used to measure a corporation’s marketing expenditure against the European Union Corporate Sustainability Reporting Directive (CSRD).

[0120] In yet another further embodiment, system 100 and methods 200-1 and 200-2 may also enable corporations to determine whether or not to increase marketing investment into a minority owned or minority-supporting media outlets..

[0121] In yet another embodiment, system 100 and methods 200- 1 and 200-2 may further provide input as to whether to upweight or downweight domains or websites as part of a corporation’s portfolio, based on the ethical media index score 900, the corporate score 904, the advertising score 908 and the content score 912. Upweighting or downweigting the scores for domains or websites allows for a determination or recommendation as to which domains or websites the advertisements may be playing on, and what inventory of domains to purchase to play said advertisements. In other embodiments, the upweighting or downweighting of scores mayallow an ad buying platform to automatically purchase advertising space on domains with a higher ethical media index score 900. More specifically, the resultant data may automatically optimize the corporation’s portfolio through the purchase of advertising spaces on domains or websites with a higher ethical media index score 900. The step of automatically determining which advertising spaces on the domains or websites to purchase also allows for a continuous self updating system. Specifically, by automatically determining which ad spaces to purchase, the ethical media index score 900 for the domains and websites within the portfolio would increase, which further leads back to the automatic determination of which ad spaces to purchase to again grant a higher ethical media index score.

[0122] For clarity, an embodiment of system 100 and methods 200-1 and 200-2 includes where the resultant ethical media index scores 900 are automatically used for the purchasing or removal of domains, websites or media sources for advertising. An example of this may either be performed by increasing the average ethical media index score 900 in every iteration of purchasing or removal of domains, websites or media sources for advertising. An alternate example of this is ensuring that the ethical media index scores 900 are above a certain threshold, leading to the automatic purchasing or removal of domains, websites, or media sources for advertising.

[0123] Media platforms and digital advertising campaigns typically have a large number of assets, or contain several thousand web domains. However, within said several thousand domains, there may be missing or incomplete information regarding the domains’ ethicality, or any other metrics that are related to the domains’ ethicality. Furthermore, the values or metrics associated with the domains’ ethicality may not be consistent as they are retrieved or provided by different sources. All of said sources may also further have a different way of viewing and / or measuring ethicality of a domain.

[0124] With several thousand web domains, each with potentially missing or incomplete values / measurement data for each domain, and each further with a different way of measuring a metric, it is impossible to have a universal compactor, or a homogeneous metric comparator of metrics for ethicality with prior methods or prior systems. A universal comparator will aid a user in being able to compare the ethicality of domains and make decisions of whether to add, remove or continue using a domain for the purposes of advertising.

[0125] In alternate embodiments, ethical media index scores 900 and the metrics / measurements that make up the ethical media index scores 900 may be requested or extracted via API to be utilized in other systems.

[0126] Ethical media index score 900 may help increase advertising investment towards Ethical Media, help grow ethical media channels, and may further encourage and normalize sustainable consumer behaviours.

[0127] Although the foregoing description and accompanying drawings to specific preferred embodiments of the present invention as presently contemplated by the inventor, it will be understood that various changes, modifications and adaptations, may be made without departing from the spirit of the invention.THE EMBODIMENTS FOR WHICH AN EXCLUSIVE PRIVILEGE OR PROPERTY IS CLAIMED ARE AS FOLLOWS:1. A method of operating an ethical media index scoring engine to evaluate the ethicality of a digital media advertising domain, the method comprising: receiving data via a communications interface from a plurality of servers; analysing the data for missing values; if values are missing: replacing the missing values in the data based on a schema; and updating a confidence score value; normalizing the data based on the schema with weighting factors via a scoring module; aggregating a normalized data into an ethical media index score via the scoring module; displaying the ethical media index score on a graphical user interface to aid a user in making a decision whether to advertise on the domain.2. The method of claim 1 , wherein analysing the data for missing values includes determining if values from the data are missing or incomplete.3. The method of claim 1, wherein replacing the missing values in the data based on the schema includes determining a type of metric of the missing value; determining a replacement value based on the type of metric from the schema; and substituting the missing value with the replacement value.4. The method of claim 1, wherein replacing the missing values in the data based on the schema includes determining a type of metric of the missing value; determining a replacement function based on the type of metric from the schema; calculating a replacement value to substitute for the missing value using the replacement function; and substituting the missing value with the replacement value.5. The method of claim 1, wherein replacing the missing values in the data based on the scheme includes determining a type of metric of the missing value; determining a replacement

Claims

coding module based on the type of metric from the schema; determining a replacement value to substitute for the missing value using the replacement coding module; and substituting the missing value with the replacement value.

6. The method of claim 1 , wherein updating the confidence score value, where the confidence score value is a first confidence score value, includes determining a type of metric of the missing value; determining the weight of the missing value based on the type of metric from the schema; and calculating a second confidence score value by reducing the first confidence score value by the weight of the missing value.

7. The method of claim 1 , wherein normalizing the data based on the schema with weighting factors via the scoring module includes determining a type of metric of the data being normalized; determining the weight of the data based on the type of metric from the schema; and calculating the normalized data based on the retrieved weight from the schema.

8. The method of claim 1, wherein aggregating a normalized data into an ethical media index score includes aggregating the normalized data of a plurality of types of metrics.

9. The method of claim 8, wherein the plurality of types of metrics includes at least a corporate score, a content score and an advertising score.

10. The method of claim 1 further comprising analyzing the ethical media index score for an advertising portfolio of multiple domains to aid a user in determining whether to add or remove domains from the advertising portfolio.

11. A system for evaluating ethicality of a domain, the system comprising: a communications interface connected to a network, wherein the communications interface is configured to receive data from a plurality of servers; a memory storage unit including:a schema providing instructions on replacing missing values in the data received from the plurality of servers, updating a confidence score value and instructions for weighting and normalizing the data; and a scoring module; a processor connected to the communications interface and the memory storage unit, the processor configured to: normalize the data with weighting factors based on the schema via the scoring module; aggregate the data into an ethical media index score via the scoring module; and display the ethical media index score on a graphical user interface to aid a user in making a decision whether to advertise on the domain.

12. The system of claim 11 , wherein the instructions of the schema on replacing missing values in the data includes instructions for replacing missing or incomplete data.

13. The system of claim 11, wherein the schema includes a type of metric and a replacement value based on the type of metric, where if values are missing or incomplete from the data received from the plurality of servers, the processor further configured to: determine the type of metric of the missing value; determine the replacement value based on the type of metric from the schema; and substitute the missing value with the replacement value.

14. The system of claim 11, wherein the schema includes a type of metric and a replacement function based on the type of metric, where if values are missing or incomplete from the data received from the plurality of servers, the processor further configured to: determine the type of metric of the missing value; determine the replacement function based on the type of metric from the schema; calculate a replacement value using the replacement function; and substitute the missing value with the replacement value.

15. The system of claim 11, wherein the schema includes a type of metric and a replacement coding module based on the type of metric, where if values are missing or incomplete from the data received from the plurality of servers, the processor further configured to: determine the type of metric of the missing value; determine the replacement coding module based on the type of metric from the schema; determine a replacement value using the replacement coding module; and substitute the missing value with the replacement value.

16. The system of claim 11, wherein the schema includes a type of metric and a weight for each type of metric, where if values are missing or incomplete from the data received from the plurality of servers, the processor further configured to: determine the type of metric of the missing value; determine the weight of the missing value based on the type of metric from the schema; and calculating a new confidence score value by reducing the prior confidence score value by the weight of the missing value.

17. The system of claim 11, wherein the schema includes the type of metric and a weight for each type of metric, wherein the processor configured to normalize the data with weighting factors based on the schema via the scoring module includes: determine the type of metric of the data being normalized; determine the weight of the data based on the type of metric from the schema; and calculate the normalized data based on the retrieved weight from the schema.

18. The system of claim 11, wherein the processor configured to aggregate the data into an ethical media index score includes aggregating the normalized data of a plurality of types of metrics.

19. The system of claim 18, wherein the plurality of types of metrics includes at least a corporate score, a content score and an advertising score.

20. The system of claim 11, wherein the memory storage unit further includes an advertising portfolio of multiple domains, wherein the processor is further configured to analyze the ethical media index score for the advertising portfolio of multiple domains to aid a user in determining whether to add or remove domains from the advertising portfolio.

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