Computer-implemented method, computer program, computer system, and computer-readable recording medium

Abstract

To arbitrate between a social network and a paid curated content.SOLUTION: A computer receives from a social network system a request for curated content, where the curated content is related to misinformative content that has been identified by the social network system. The computer sends to a system of a paid curated content producer a request for making the curated content public. In response, the system of the paid curated content producer accepts the request for making the curated content public, and the computer provides to the social network system a link to the curated content on the system of the paid curated content producer. On the social network system, a computer-implemented method is used to flag the misinformative content and present the link to the curated content other than the misinformative content.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention generally relates to the reduction of misinformation content in social networks, and more specifically, to the reduction of misinformation content by mediating between a social network and producers of paid curated content.

Background Art

[0002] Separate from all existing efforts to identify bias in social networks and classify content shared in instant messaging applications as misinformation content or misinformation, there is still a need to prevent misinformation content or misinformation that has gone viral (or is virally spreading) in social networks. In many cases, curated content (or trusted content) that can counter misinformation lies behind a paywall (an access restriction provided by a paid content provider after free or more liberal access).

[0003] U.S. Patent No. 9,852,376 (Donoho, 2015) (Patent Document 1) teaches a method and apparatus for proving facts; the method and apparatus introduce a certifier and fact proof within a fact exchange cycle that enables an organization to exchange with reliable facts. U.S. Patent No. 10,062,091 (Schwimmer, 2013) (Patent Document 2) discloses a system and method for enabling a website publisher to integrate a website paywall system into an additional content server system of the website. U.S. Patent No. 8,423,424 (Myslinski, 2012) (Patent Document 3) discloses a web page fact checking system that verifies the accuracy of information and either characterizes the information or both by comparing the information with one or more sources. U.S. Patent Publication No. 2014 / 0164994 (Myslinski, 2013) (Patent Document 4) describes a fact checking system that automatically monitors, processes, and fact checks information, and this fact checking system can add a graphical user interface having a fact check icon indicating the result of the fact check. However, none of the above disclosures provide a solution for reducing misinformation content shared through mediation between a social network and a trusted source for generating curated content.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Patent Document 3

Patent Document 4

Summary of the Invention

Problems to be Solved by the Invention

[0005] The present invention aims to provide mediation between a social network in reducing misinformation content and producers of paid curated content.

Means for Solving the Problems

[0006] In one aspect, a computer-implemented method for reducing misinformation content is provided. The computer-implemented method includes receiving a request for curated content from a social network system, where the curated content is related to misinformation content identified by the social network system. The computer-implemented method further includes sending a request to the system of the producer of the paid curated content to publish the curated content. The computer-implemented method further includes, in response to the system of the producer of the paid curated content accepting the request to publish, providing a link to on the system of the producer of the paid curated content to the social network system. By the computer-implemented method on the social network system, misinformation content is flagged and a link to the curated content is presented separately from the misinformation content. Selected Content In response to the system of the producer of the paid curated content accepting the request to publish, providing a link to on the system of the producer of the paid curated content to the social network system. Selected Content The computer-implemented method further includes identifying misinformation content by the social network system; identifying a topic of the misinformation content by the social network system; transmitting the misinformation content, the topic, and network information of the social network system by the social network system; and transmitting a request for curated content by the social network system. In the computer-implemented method, the network information includes at least one of graph topology criteria and characteristics of the social network system.

[0007] The computer-implemented method further includes identifying misinformation content by the social network system; identifying a topic of the misinformation content by the social network system; transmitting the misinformation content, the topic, and network information of the social network system by the social network system; and transmitting a request for curated content by the social network system. In the computer-implemented method, the network information includes at least one of graph topology criteria and characteristics of the social network system.

[0008] The computer-implemented method further includes predicting the reach of misinformation content based on topics and network information. The computer-implemented method further includes retrieving premium selected content from one or more systems of each producer of the premium selected content. The computer-implemented method further includes ranking one or more systems of each producer of the premium selected content based on the user orientation for each producer of the premium selected content. The computer-implemented method further includes selecting the system of the producer of the premium selected content from one or more systems of each producer of the premium selected content based on the ranking of one or more systems of each producer of the premium selected content.

[0009] The computer-implemented method further includes predicting, by a user of the social network system, the number of visits to one or more systems of each producer of the premium selected content. Selected Content The computer-implemented method further includes notifying the number of visits to the system of the producer of the premium selected content and sending a request to publish the premium selected content to the system of the producer of the premium selected content. In the computer-implemented method, the system of the producer of the premium selected content, based on the number of visits, determines whether to remove the paywall for the premium selected content.

[0010] The computer-implemented method further includes, in response to there being no premium selected content available on the system of the producer of the premium selected content, requesting the production of premium selected content for countering misinformation content from the system of the producer of the premium selected content.

[0011] In another aspect, a computer-readable recording medium and a computer program for reducing misinformation content are provided. The computer program is stored in a computer-readable recording medium in which program instructions are embedded, and the program instructions are executable by one or more processors. The program instructions are to receive a request for curated content related to misinformation content identified by a social network system from the social network system; send a request to the system of the producer of the charged curated content to publish the curated content; in response to the system of the producer of the charged curated content allowing the request to publish the curated content, flag the misinformation content on the social network system and present a link to the curated content separately from the misinformation content, and provide the social network system with a link to the curated content on the system of the producer of the charged curated content.

[0012] In the computer program, the program instructions are further executable to identify misinformation content by the social network system. In the computer program, the program instructions are further executable to identify a topic of misinformation content by the social network system. In the computer program, the program instructions are further executable to enable the social network system to send misinformation content, a topic, and network information of the social network system, where the network information includes at least one of the graph topology criteria and features of the social network system. In the computer program, the program instructions are further executable to send a request for curated content by the social network system.

[0013] In a computer program, the program instructions are further capable of predicting the reach of misinformation content based on topics and network information; retrieving premium content from one or more systems of each producer of premium content that is charged; ranking one or more systems of each producer of premium content based on the user orientation for each producer of premium content that is charged; and selecting a system of a producer of premium content from one or more systems of each producer of premium content that is charged based on the ranking of one or more systems of each producer of premium content that is charged.

[0014] In a computer program, the program instructions are further capable of predicting the number of visits to one or more systems of each producer of premium content that is charged on a social network system by users of the social network system; and notifying the system of a producer of premium content of the number of visits and sending a request to publish premium content. Based on the number of visits, the system of a producer of premium content determines whether to remove the paywall for the premium content. Selected Content In a computer program, the program instructions are further capable of, in response to there being no premium content available on the system of a producer of premium content that is charged, requesting the system of a producer of premium content that is charged to generate premium content to counter misinformation content.

[0015] In a computer program, the program instructions are further capable of, in response to there being no premium content available on the system of a producer of premium content that is charged, requesting the system of a producer of premium content that is charged to generate premium content to counter misinformation content.

[0016] In yet another aspect, a computer system for reducing misinformation content is provided. The computer system includes one or more processors; one or more computer-readable tangible storage devices; and program instructions stored in at least one of the one or more computer-readable tangible storage devices for execution by at least one of the processors. The program instructions are executable to receive a request for curated content related to misinformation content identified by a social network system from the social network system. The program instructions are further executable to send a request to the system of the producer of the paid curated content to publish the curated content. In response to the system of the producer of the paid curated content accepting the request to publish the curated content, the program instructions are further executable to provide a link to the curated content on the system of the producer of the paid curated content to the social network system. On the social network system, the misinformation content is flagged and the link to the curated content is presented separately from the misinformation content.

[0017] In the computer system, the program instructions are further executable to identify misinformation content by the social network system; identify the topic of the misinformation content by the social network system; send the misinformation content, the topic, and the network information of the social network system by the social network system; and send a request for curated content by the social network system. The network information includes at least one of graph topology criteria and characteristics of the social network system.

[0018] In a computer system, program instructions are further capable of predicting the arrival of misinformation content based on topics and network information. In a computer system, program instructions are further capable of retrieving premium content from one or more systems of each producer of the premium content that has been charged. In a computer system, program instructions can further rank one or more systems of each producer of the premium content that has been charged based on the user orientation for each producer of the premium content that has been charged. In a computer system, program instructions are further capable of selecting producers of the premium content that has been charged from one or more systems of each producer of the premium content that has been charged based on the ranking of one or more systems of each producer of the premium content that has been charged.

[0019] In a computer system, program instructions are further capable of predicting the number of visits to one or more systems of each producer of the premium content that has been charged by users of the social network system. Selected Content In a computer system, program instructions can further notify the number of visits to the system of the producer of the premium content that has been charged and send a request to publish the premium content to the system of the producer of the premium content that has been charged. In the computer system, based on the number of visits, the system of the producer of the premium content that has been charged determines whether to remove the paywall for the premium content.

[0020] In a computer system, program instructions are further capable of, in response to there being no premium content available on the system of the producer of the premium content that has been charged, requesting the system of the producer of the premium content that has been charged to generate premium content to counter the misinformation content.

Brief Description of the Drawings

[0021]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Mode for Carrying Out the Invention

[0022] Embodiments of the present invention disclose a technology that bridges a social network (where misinformation can go viral or spread virally) and producers of curated content (opposite of misinformation content). In embodiments of the present invention, the system mediates between a social network system and a trusted source or producer of curated content to reduce the sharing of misinformation content. The purpose of the system is to enable free access to curated content (often behind a paywall) that can prevent the spread of misinformation content (with the potential to go viral). The present invention provides a solution that controls the handshake between a social network system and a trusted resource, providing the advantage of preventing the spread of misinformation content diffusion to the social network system, thereby enabling a perfect connection or visualization for trusted resources (often related to advertising and reputation or image value) that would otherwise be inaccessible without the access flow from the social network system. The technology disclosed in embodiments of the present invention considers a number of components for (1) crawling the content required by the social network and trusted resources, (2) calculating the viral (or viral spread) factor of misinformation content based on the graph topology of the social network system, and (3) converting to the potential perfect connections or viewings generated for trusted resources when the identified curated content is opened.

[0023] The present invention proposes a method for benefiting both side - social network systems and trusted resources. The proposed system identifies misinformation content. The proposed system identifies the likelihood of the misinformation content going viral and the need for curated content that trusted resources should submit. In the proposed system, the trusted resources remove paywall control for the curated content, and the social network system can recommend and display curated content separately from the misinformation content classified as being misinformative. Thus, users of the social network system have the opportunity to access curated and trustworthy content before sharing misinformation content that has a high likelihood of going viral or spreading virally.

[0024] FIG. 1 is a system diagram showing a system 100 that mediates between a social network and producers of paid curated content in misinformation content reduction according to an embodiment of the present invention. System 100 includes a plurality of user devices (110 - 1, 110 - 2,..., and 110 - N). System 100 further includes a social network system 120, a central entity 130, and a trusted source or producer 140 of paid curated content.

[0025] Each one of the user devices (110 - 1, 110 - 2,..., and 110 - N) is a computing device such as, for example, a desktop computer and a mobile device. Each one of the user devices (110 - 1, 110 - 2,..., and 110 - N) can be an electrical device or a computing system that receives input from a user, executes computer program instructions, and can communicate with another computing system via a network. The computing device will be described in more detail in a later paragraph with reference to FIG. 3.

[0026] The social network system 120, the central entity 130, or the trusted source 140 can exist on a computing device or a server. In another embodiment, the social network system 120, the central entity 130, or the trusted source 140 can exist on a virtual machine or another virtualization implementation. The virtual machine or the virtualization implementation operates on a computing device. The virtual machine or the virtualization implementation will be described in more detail with reference to FIG. 3 in a later paragraph.

[0027] The system 100 can be implemented in a network that can support any combination of a plurality of connections and a plurality of protocols for communication between the user devices (110-1, 110-2,..., and 110-N), the social network system 120, the central entity 130, and the trusted source 140. For example, the network can be implemented as the Internet, which represents a worldwide aggregation of networks and gateways for supporting communication between devices connected to the Internet; the network can be implemented as an intranet, a local area network (LAN), a wide area network (WAN), and a wireless network. The system 100 can be implemented in a cloud computing environment. The cloud computing environment will be described in detail in a later paragraph with reference to FIGS. 4 and 5.

[0028] Figure 1 should be understood to provide only an illustration of a system that mediates between a social network in reducing misinformation content and producers of paid, curated content. Figure 1 illustrates an embodiment of a system that includes one social network system and one source of trust. It should be understood that the system can have one or more social network systems and one or more sources of trust. One or more social network systems can exist on different computing devices or servers, and one or more sources of trust can also exist on different computing devices or servers.

[0029] Users of the social network system 120 use user devices (110-1, 110-2,..., and 110-N) to access content on the social network system 120. Some of the content on the social network system 120 will be misinformation. The social network system 120 includes a misinformation content classification function for identifying misinformation content on the social network system 120. The social network system 120 sends a request for curated and trusted content to a central entity 130. Curated and trusted content often exists behind a paywall on a source of trust 140. Along with the request, the social network system 120 sends network information such as the identified misinformation content, the topic of the misinformation content, and the topology of the social network system.

[0030] The central entity 130 receives requests for selected and trusted content. The central entity 130 includes a module for virus evaluation or for calculating a virality factor based on misinformation topics and the topology of the social network system; thus the central entity 130 can predict the arrival of misinformation content. The central entity 130 further includes a crawler that is requested by the social network system 120 and crawls the selected and trusted content available on the trusted source 140. The central entity 130 further includes a module for predicting well-matched connections (the user access flow from the social network system 120 to the trusted source 140) or for predicting the number of visits to the selected content on the trusted source 140 from the users of the social network system 120.

[0031] To speed up the crawl process on the social network system 120, a configuration file is placed in the root directory on the social network system 120. For example, the configuration file on the social network system 120 can be a published text file or JavaScript Object Notation (JSON). The configuration file contains a list of misinformation content. Each record of the configuration file can include the uniform resource locator (URL) of the misinformation content and the topic of the misinformation content presented within this URL. Similarly, the configuration file is placed in the root directory of the crawl process on the trusted source (system of producers of paid premium content) 140. For example, the configuration file on the trusted source (system of producers of paid premium content) 140 can be a text file or JavaScript Object Notation (JSON). The configuration file contains a list of premium content. Each record of the configuration file can include the uniform resource locator (URL) of the premium content and the topic of the premium content presented within that URL. The configuration file on the social network system 120 or the trusted source (system of producers of paid premium content) 140 enables the crawler function on the central entity 130 to perform timely analysis before misinformation content becomes viral (spreads virally).

[0032] The central entity 130 mediates between the social network system 120 and the trusted source 140. The central entity 130 sends a prediction of a precise connection to the trusted source 140 and also sends a request to the trusted source 140 to remove the paywall or to publish selected and trusted content.

[0033] The trust source 140 includes a paywall control function unit. When receiving a request to remove the paywall from the central entity 130, the trust source 140 determines whether to allow the request to remove the paywall. In response to the decision to allow this request, the paywall control function of the trust source 140 is selected to remove the paywall for the selected and trusted content.

[0034] On the social network system 120, the central entity 130 is selected to suggest to the user a link to the trust source 140 that provides selected and trusted content. On the social network system 120, misinformation content is flagged and a link to the selected and trusted content is added separately from the misinformation content. Through mediation between the social network system 120 by the central entity 130 and the trust source 140, the user of the social network system 120 can avoid the paywall on the trust source 140 and have access to the selected and trusted content. When the user uses the user devices (110-1, 110-2,..., and 110-N) to access the selected and trusted content (related to misinformation content), the personal perspectives and opinions on the topic become rich, and thus the sharing of misinformation content is reduced.

[0035] FIG. 2 is a flowchart showing the operation steps of mediation between the social network and the producer of the charged selected content in reducing misinformation content in one embodiment of the present invention. The operation steps are implemented by one or more processors on one or more computing devices or servers.

[0036] In step 201, a social network system (such as the social network system 120 in the embodiment shown in FIG. 1) identifies misinformation content on the social network system. The misinformation content may be shared within the instant messaging application of a user of the social network system. Content shared on the social network system (such as images, text, audio, and video in a post) is submitted to the misinformation content classification function unit on the social network system. In response to a high probability (certainty threshold) that the content is misinformation, the misinformation content classification function unit internally flags the content as misinformation.

[0037] In step 202, the social network system identifies the topic of the misinformation content. Using natural language processing (NLP) methods, the social network system extracts the topic of the misinformation content investigated and further identifies it on an external website. The topic can be used to better identify the object related to the misinformation content.

[0038] In step 203, the social network system requests the central entity (such as the central entity 130 in the embodiment shown in FIG. 1) for curated content. In sending the request for curated content, the social network system sends the misinformation content (identified in step 201), the topic (identified in step 202), and the network information of the social network system to the central entity. The network information includes, without limitation, graph topology criteria or characteristics (such as average degree, diameter, betweenness, and proximity).

[0039] The central entity receives a request for curated content from the social network system. In step 204, the central entity predicts the arrival of misinformation content based on the topics and network information provided by the social network system. Using the information on well - matched connections provided by the social network system (e.g., the number of "likes" and views or both) and graph topology or network criteria (e.g., influence, centrality), the central entity calculates the arrival of the investigated misinformation content.

[0040] In step 205, the central entity searches for curated content from one or more trusted sources (producers of each paid curated content or one or more systems) based on the topic. The trusted source 140 in the embodiment shown in FIG. 1 is one of the one or more trusted sources. The curated content requested by the social network system is available on one or more trusted sources. The central entity requests the social network system for a document that can refute or confirm the topic sent by the social network system.

[0041] In step 206, the central entity predicts the number of visits by users of the social network system to the curated content on the trusted source. To predict the number of visits to the curated content, the central entity calculates a conversion criterion (e.g., click - through rate) based on the access history of similar curated content by users of the social network system. In step 207, the central entity ranks one or more sources based on the user orientation for the trusted source.

[0042] Based on the ranking of one or more trusted sources, the central entity selects trusted sources from one or more trusted sources. In step 208, the central entity sends a request to the selected trusted sources to publish the curated content (or remove the paywall for the curated content). The central entity also notifies the selected trusted sources of the number of visits to the curated content by users of the social network system. The central entity determines access to the curated content on the selected trusted sources by providing information about potential viewers who may be from the social network system.

[0043] Based on the information provided by the central entity, the selected trusted source determines whether to remove the paywall for the curated content. In step 209, the selected trusted source accepts the request to publish the curated content. The selected trusted source notifies the central entity that the paywall for the requested curated content has been removed, so that the requested curated content can be presented or recommended separately from the identified misinformation content. If the selected trusted source rejects the request to publish the curated content, the curated content remains controlled by the paywall of the selected trusted source until one of the one or more selected trusted sources accepts the request to publish the curated content; and the central entity finds a new trusted source.

[0044] In step 210, the central entity provides a link to curated content on a selected trusted source for the social network system. For example, the central entity provides a Uniform Resource Locator (URL) of the curated content on the selected trusted source for the social network system. In step 211, the social network system flags the misinformation content. In step 212, the social network system presents the link to the curated content on the selected trusted source separately from the misinformation content.

[0045] In other embodiments, in response to one or more trusted sources having no results for the central entity's query at all, the central entity searches for results related to the original query and then crawls the Web. In still other embodiments, in response to one or more trusted sources having no results for the central entity's query at all, the central entity requests the generation of curated content for refuting or endorsing the misinformation content for one or more trusted sources.

[0046] FIG. 3 is a diagram showing the components of a computing device or server according to one embodiment of the present invention. It should be understood that FIG. 3 merely illustrates one implementation and does not mean any limitation regarding the environment in which different embodiments can be implemented.

[0047] Referring to FIG. 3, a computing device or server 300 includes a processor (which may be plural) 320 and a tangible memory device (which may be plural) 330. In FIG. 3, the communication between the above-described components of the computing device or server 300 is indicated by reference numeral 390. Memory 310 includes a ROM (Read Only Memory) (which may be plural) 311, a RAM (Random Access Memory) (which may be plural) 313, and a cache (which may be plural) 315. One or more operating systems 331 and one or more computer programs 333 are present in one or more computer-readable tangible memory devices (which may be plural) 330.

[0048] The computing device or server 300 further includes an I / O interface (which may be plural) 350. The I / O interface (which may be plural) 350 enables input and output of data with external devices (which may be plural) 360 that can be connected to the computing device or server 300. The computing device or server 300 further includes a network interface (which may be plural) 340 for communication between the computing device or server 300 and a computer network.

[0049] The present invention can be a system, a method, a computer-readable recording medium or a computer program, and combinations thereof, at any possible technically detailed level of integration. The computer-readable recording medium (or media) and the computer program have computer-readable program instructions for a processor to perform the features of the present invention.

[0050] A computer-readable recording medium can be a tangible device that can hold and store multiple instructions for use by an instruction execution device. A computer-readable medium can be, for example, but not limited to, an electrical recording device, a magnetic recording device, an optical recording device, an electro-magnetic recording device, a semiconductor recording device, or any preferred combination thereof. More specific examples of a computer-readable recording medium include, but are not limited to, the following: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory (registered trademark)), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk (registered trademark), a punch card, or a mechanically encoded device having a structure that protrudes into a groove in which instructions are recorded, and any preferred combination thereof. As used herein, a computer-readable recording medium is not itself interpreted as a transient signal such as a radio wave or other freely propagating electromagnetic wave, a waveguide or other communication medium (e.g., an optical pulse passing through an optical fiber cable), or an electrical signal communicated through a wire.

[0051] The computer programs described in this specification can be downloaded from a computer-readable recording medium to respective computing / processing devices, or can be downloaded to an external computer or an external recording device via a network such as, for example, the Internet, a local area network, a wide area network, or a wireless network and combinations thereof. The network can include copper communication cables, optical communication fibers, wireless communication routers, firewalls, switches, gateway computers, and edge servers or combinations thereof. A network adapter card or network interface in each computing / processing device receives computer-readable program instructions from the network and transfers the computer-readable program instructions to a computer-readable recording medium within each computing / processing device for storage thereof.

[0052] Computer-readable program instructions for carrying out the operations of the present invention may be source code or object code written in any combination of programming languages, including assembly instructions, instruction set architecture (ISA) instructions, machine language instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuits, or one or more procedural programming languages such as the object-oriented programming languages of Smalltalk®, C++, the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN), a wide area network (WAN), or the connection may be made to an external computer (e.g., through an Internet service provider). In some embodiments, an electrical circuit, including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), can personalize and execute the electrical circuit using the state information of the computer-readable program instructions to perform the features of the present invention.

[0053] The features of the present invention described herein have been described with reference to flowchart instructions and block diagrams of methods, or both, apparatus (systems), and computer-readable recording media and computer programs, in accordance with embodiments of the present invention. It should be understood that any combination of the flowchart illustrations and block diagrams, or both, and blocks in the flowchart illustrations and block diagrams, or both, can be implemented by computer-readable program instructions.

[0054] Computer-readable program instructions can be provided to a computer's processor or other programmable data processing apparatus for generating a computer, and cause the functions / operations specified by blocks or multiple blocks in a flowchart and block diagram or combinations thereof to be implemented by execution by the computer's processor or other programmable data processing apparatus. These computer-readable program instructions that direct a computer, programmable data processing apparatus, and other devices or combinations thereof to function in a particular manner can also be stored in a computer-readable recording medium, and the computer-readable recording medium storing the instructions constitutes a manufactured article including instructions for implementing the features of the functions / operations specified by blocks or multiple blocks in a flowchart and block diagram or combinations thereof.

[0055] Computer-readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device, causing a computer-implemented process to occur for a series of operation steps on the computer, other programmable apparatus, or other device, thereby implementing the functions / operations specified by blocks or multiple blocks in a flowchart and block diagram or combinations thereof on the computer, other programmable apparatus, or other device.

[0056] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and possible implementation operations of systems, methods, and computer programs according to various embodiments of the present invention. In this regard, a flowchart or block diagram can represent a module, segment, or portion of instructions, which include one or more executable instructions for implementing a particular logical function (or functions). In some alternative implementations, the functions described in the blocks can be executed differently than shown. For example, two blocks shown in succession can, depending on the functions involved, actually be performed as one step, executed simultaneously, substantially simultaneously, partially or completely overlapping in time, or the blocks can sometimes be executed in reverse order. Also, the illustration of the block diagrams and flowcharts, or both of them and the blocks in the block diagrams and the illustration of the flowcharts or combinations thereof, indicate that they can be implemented by a system based on specific hardware for performing a specific function or operation or for performing specific hardware and computer instructions for a particular purpose.

[0057] The present disclosure includes a detailed description of cloud computing, but it should be understood that the implementation of the teachings recited in the present disclosure is not limited to cloud computing. Rather, embodiments of the present invention can be implemented in combination with any other type of computing environment known heretofore or developed hereafter.

[0058] Cloud computing is a service delivery model for on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model can include at least five characteristics, at least three service models, and at least four deployment models.

[0059] The characteristics are as follows:

[0060] On-demand self-service: Cloud consumers can unilaterally and automatically obtain as much computing power as needed, such as server time and network storage, without the need for human interaction with the service provider.

[0061] Broad network access: Capabilities are available over the network and accessed through standard mechanisms that promote use by different thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

[0062] Resource pooling: Provider computing resources are pooled to serve multiple consumers with different physical and virtualized resources that are dynamically assigned and reassigned as needed. There is a sense of location independence in that consumers generally have no control or knowledge of the exact location of the provided resources (e.g., country, state, or data center) and can specify location at a high level of abstraction.

[0063] Rapid elasticity: The function can be supplied quickly and elastically, and in some cases automatically, scale out quickly, and release quickly and scale in quickly. For consumers, the functions available for supply often seem to have no restrictions and can be purchased in any quantity at any time.

[0064] Measured services: Cloud systems automatically control and optimize resource usage by leveraging metering functions at several levels of abstraction suitable for service types (e.g., storage, processing, bandwidth, and active user accounts). By monitoring, controlling, and reporting resource usage, transparency can be provided to both the providers and consumers of the services being used.

[0065] The service model is as follows:

[0066] Software as a Service (SaaS): The function provided to the consumer is to use the provider's application running on the cloud infrastructure. The application is accessible from various client devices through a thin-client interface such as a web browser (e.g., web-based email). The consumer does not manage or control the underlying cloud infrastructure, including the network, server, operating system, storage, or the functions of individual applications, except for limited user-specific application configuration settings.

[0067] Platform as a Service (PaaS): The capabilities provided to the consumer are to place the applications created or acquired by the consumer, which are created using the programming languages and tools supported by the provider, onto the cloud infrastructure. The consumer does not manage or control the underlying cloud infrastructure, which includes the network, servers, operating systems, or storage, but controls the deployed applications and, if possible, configures the application hosting environment.

[0068] Infrastructure as a Service (IaaS): The functions provided to the consumer are the provision of processing, storage, network, and other basic computing resources, and the consumer can deploy and run any software that can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure, but has control over the operating systems, storage, deployed applications, and, if possible, has limited control over selected networking components (e.g., the host firewall).

[0069] The deployment models are as follows.

[0070] Private cloud: The cloud infrastructure operates only for one organization. It can be managed by that organization or a third party and can exist on - premise or off - premise.

[0071] Community Cloud: The cloud infrastructure is shared by several organizations and supports a specific community with common interests (e.g., mission, security requirements, policies, and compliance considerations). It can be managed by those organizations or a third party and can exist on-premises or off-premises.

[0072] Public Cloud: The cloud infrastructure is made available to the general public or a large industry group and is owned by an organization that sells cloud services.

[0073] Hybrid Cloud: The cloud infrastructure is a combination of two or more clouds (private, community, or public), which remain distinct entities but are connected to each other by standardized or proprietary technologies that enable data and application portability (e.g., cloud bursting for load balancing between clouds).

[0074] Cloud software is service-oriented, focusing on statelessness, loose coupling, modularity, and semantic interoperability. At the heart of cloud computing is the infrastructure, which includes multiple interconnected nodes.

[0075] Referring to FIG. 4, an exemplary cloud computing environment 50 is shown. As illustrated, cloud computing environment 50 includes one or more cloud computing nodes 10 that communicate with local computing devices such as, for example, a personal digital assistant (PDA) or cellular telephone 54a, desktop computer 54B, laptop computer 54C, or automotive computer system 54N or a combination thereof, used by cloud consumers. The cloud computing nodes 10 can communicate with one another. These can be physically or virtually grouped (not shown) within one or more networks such as the private, community, public, or hybrid clouds described above, or a combination thereof. The types of computing devices 54A-N shown in FIG. 2 are for illustrative purposes only, and it is understood that the cloud computing nodes 10 and the cloud computing environment 50 can communicate with any type of computerized device through any type of network or addressable network connection (e.g., a web browser), or both.

[0076] Now referring to FIG. 5, a set of functional abstraction layers provided by cloud computing environment 50 (FIG. 4) is shown. It should be understood that the components, layers, and functions shown in FIG. 5 are for illustrative purposes only and that embodiments of the invention are not limited thereto. As shown, the layers and corresponding functions described below are provided.

[0077] The hardware and software layer 60 includes hardware and software components. Examples of hardware components can include a mainframe 61; multiple servers 62 based on a RISC (Reduced Instruction Set Computer) architecture; multiple servers 63; multiple blade servers 64; multiple storage devices 65; and networks and networking components 66. In some embodiments, the software components can include network application server software 67 and database software 68.

[0078] The visualization layer 70 provides an abstract layer where examples of virtual entities to be described later are provided; virtual servers 71; virtual storage 72; a virtual network 73 including a virtual private network; virtual applications and operating systems 74; and virtual clients 75.

[0079] In one embodiment, the management layer 80 can provide the following functions. The resource provider 81 provides for the dynamic acquisition of computing resources and other resources used to perform tasks within a cloud computing environment. The measurement and pricing unit 82 provides cost tracking when resources are used within the cloud computing environment and provides billing or invoicing for the consumption of these resources. In one embodiment, these resources can include application software licenses. The security unit provides protection of data and other resources along with the identification and authentication of cloud consumers and tasks. The user portal unit 83 provides accessibility to the cloud computing environment for consumers and to the system administrator. The service level management unit 84 provides for the allocation and management of cloud computing resources and conforms to the required service levels. The service level agreement (SLA) planning and fulfillment unit 85 makes advance preparations for and acquires cloud computing resources required by future demands according to the SLA.

[0080] The workload layer 90 provides an exemplification of functions for utilizing a cloud computing environment. Examples of workloads and functions provided by this layer can include mapping and navigation 91; software development and lifetime management 92; virtual classroom education delivery 93; data analysis processing 94; transaction processing 95; and function 96. Function 96 in the present invention is a function that mediates between a social network and producers of paid-for selected content in reducing misinformation content within a cloud computing environment.

Explanation of Signs

[0081] 10: Node 50: Computing Environment 54A-N: Device 54B: Computer 54C: Laptop computer 54N: System 54a: Cellular phone 60: Software layer 61: Mainframe 62: Server 63: Server 64: Server 65: Device 66: Component 67: Software 68: Software 70: Visualization layer 71: Virtual server 72: Virtual storage 73: Virtual network 74: System 75: Virtual client 80: Layer 81: Resource providing department 82: Pricing department 83: Portal department 84: Management department 85: Fulfillment department 90: Layer 91: Navigation 92: Management 93: Virtual classroom education delivery 94: Data analysis processing 95: Processing 96: Function 100: System 120: System 130: Central entity 140: Producer 140: Trusted source

Claims

1. 1. A computer-implemented method for misinformation content reduction, the method comprising: receiving, by one or more processors, a request from a social networking system for curated content related to the misinformation content identified by the social networking system; sending, by said one or more processors, a request to a system of a producer of curated content for which a fee has been charged for the publication of said curated content; in response to the system of the fee-based curated content producer granting a request to make the curated content public, by the one or more processors, providing to the social network system a link to the curated content on the system of the fee-based curated content producer; A computer-implemented method, wherein the misinformation content is flagged on the social networking system and links to the curated content are presented separately from the misinformation content.

2. further, predicting, by said one or more processors, a number of visits by users of said social network system to each of said curated content on said one or more systems for each of said producers of said charged curated content; sending, by the one or more processors, to the system of the producer of the charged curated content, a request to publish the curated content together with notifying the system of the number of visits; The computer-implemented method of claim 1 , wherein the system of the producer of the curated content charged based on the number of visits includes determining whether to remove a paywall to the curated content.

3. further identifying, by the social network system, the misinformation content; identifying, via said social network system, topics of said misinformation content; transmitting, by the social network system, the misinformation content, the topic, and network information of the social network system; and 3. The computer-implemented method of claim 1 or 2, further comprising transmitting a request for the curated content over the social network system.

4. 4. The computer-implemented method of claim 3, wherein the network information includes at least one of a graph topology metric and a characteristic of a social network system.

5. further predicting, by the one or more processors, the arrival of the misinformation content based on the topic and the network information; retrieving, by said one or more processors, said curated content from one or more systems of each of said producers of said charged curated content; ranking, by the one or more processors, the one or more systems of each of the charged curated content producers based on user preferences for each of the charged curated content producers; and A computer-implemented method as claimed in any one of claims 3 or 4, comprising selecting, by the one or more processors, the system of the charged curated content producer from the one or more systems of each of the charged curated content producers based on a ranking of the one or more systems of each of the charged curated content producers.

6. The computer-implemented method of any one of claims 1 to 5, further comprising, in response to no curated content being available on the system of the charged curated content producer, requesting, by the one or more processors, from the system of the charged curated content producer to generate the curated content to refute the misinformation content.

7. 1. A computer program for misinformation content reduction, the computer program comprising program instructions executable by one or more processors, the computer program causing a computer to: receiving a request from a social networking system for curated content related to the misinformation content identified by the social networking system; sending a request to a system of a producer of paid curated content to make the curated content available; providing, in response to the system of the fee-paid curated content producer granting a request to make the curated content public, to the social network system a link to the curated content on the system of the fee-paid curated content producer; The misinformation content is flagged on the social networking system and links to the curated content are presented separately from the misinformation content.

8. The computer program further comprises: predicting the number of visits by users of the social network system to the curated content on the one or more systems for each of the producers of the charged curated content; notifying the system of the producer of the charged curated content of the number of visits and sending a request to have the curated content published; 8. The computer program product of claim 7, wherein based on the number of visits, the system of the paid curated content producer decides whether to remove a paywall to the curated content.

9. The program instructions further include: identifying said misinformation content with said social networking system; identifying, via said social network system, topics of said misinformation content; Sending, by the social network system, the misinformation content, the topics, and network information of the social network system; and 9. A computer program product as claimed in claim 7 or 8, which is adapted to send a request for the curated content by the social network system.

10. The computer program product of claim 9, wherein the network information includes at least one of graph topology criteria and characteristics of a social network system.

11. The computer program further comprises: predicting the reach of the misinformation content based on the topic and the network information; retrieving the curated content from the one or more systems of each of the producers of the charged curated content; ranking the one or more systems of each of the producers of paid curated content based on user preferences for each of the producers of paid curated content; and 11. A computer program product as claimed in claim 9 or 10, which is configured to select the system of the charged curated content producer from the one or more systems of each of the charged curated content producers based on a ranking of the one or more systems of each of the charged curated content producers.

12. The computer program further comprises: A computer program product as claimed in any one of claims 7 to 11, which, in response to there being no curated content available on the system of the producer of the charged curated content, requests the system of the producer of the charged curated content to generate the curated content to refute the misinformation content.

13. 1. A computer system for reducing misinformation content, the computer system including one or more processors, one or more computer readable tangible storage devices, and program instructions stored in at least one of the one or more computer readable tangible storage devices for execution by the processor(s), the computer system comprising: receiving a request from a social networking system for curated content related to the misinformation content identified by the social networking system; sending a request to the system of a producer of paid curated content to have the curated content published; providing, in response to the system of the producer of the curated content for which fees are charged, a link to the curated content on the producer of the curated content's system to the social network system, the link being responsive to the system of the producer of the curated content for which fees are charged, accepting the request to make the curated content public; A computer system, on the social networking system, where the misinformation content is flagged on the social networking system and links to the curated content are presented separately from the misinformation content.

14. moreover, predicting the number of visits by users of said social networking system to said curated content on said one or more systems of each of said producers of said charged curated content; sending a request to a system of a producer of the charged curated content to notify the system of the number of visits and to make the curated content public; 14. The computer system of claim 13, wherein based on the number of visits, the system of the paid curated content producer decides whether to remove a paywall to the curated content.

15. moreover, identifying said misinformation content with said social networking system; identifying, via said social network system, topics of said misinformation content; sending, by the social network system, the misinformation content, the topic, and network information of the social network system; 15. A computer system according to claim 13 or 14, further comprising means for sending a request for the curated content via the social network system.

16. 16. The computer system of claim 15, wherein the network information includes at least one of a graph topology metric and a characteristic of a social network system.

17. moreover, predicting the reach of the misinformation content based on the topic and the network information; retrieving said curated content from one or more systems of each of said producers of said charged curated content; performing a ranking of the one or more systems of each of the charged curated content producers based on a user preference for each of the charged curated content producers; A computer system as described in claim 15 or 16, selecting the system of the charged curated content producer from the one or more systems of each of the charged curated content producers based on a ranking of the one or more systems of each of the charged curated content producers.

18. moreover, The computer system of any one of claims 13 to 17, further comprising: in response to no curated content being available on the system of the producer of the charged curated content, the computer system executing a request to the producer of the charged curated content to generate the curated content to refute the misinformation content.

19. A computer-readable recording medium having recorded thereon a computer program for causing a computer to execute the computer-implemented method according to any one of claims 1 to 6.

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