Analysis module and method of ecological environment public opinion monitoring system of smart environmental protection platform

Abstract

The embodiment of the application discloses an analysis module and method of an ecological environment public opinion monitoring system of a smart environmental protection platform. The analysis method of the ecological environment public opinion monitoring system of the smart environmental protection platform comprises the following steps: obtaining an information special topic creation instruction selected by a user, creating an information public opinion special topic according to the information special topic creation instruction, the information special topic instruction comprising information sources and / or information search conditions, and collecting public opinion information to be analyzed according to the information special topic instruction; obtaining target public opinion information from the public opinion information to be analyzed according to keywords or sample articles corresponding to target environmental protection event setting information; analyzing the target public opinion information, obtaining an event level and a concern level of an environmental protection event corresponding to the environmental protection event setting information, and generating an environmental protection event report. The application can effectively improve the work efficiency of the user and reduce the work burden of the user.

Description

Technical Field

[0001] This invention relates to the field of environmental protection technology, and in particular to the analysis module and method of an intelligent environmental protection platform ecological environment public opinion monitoring system. Background Technology

[0002] With the widespread use of social media, online information spreads faster and more profoundly than ever before. Certain breaking events, when disseminated online, can often cause significant social impact in a very short time. Negative information, in particular, if not detected and contained in a timely manner, can lead to irreparable damage to reputation, credibility, or property, and may even cause social unrest.

[0003] To minimize such unnecessary harm, it is necessary to monitor online public opinion and assess crisis levels, thereby enabling timely crisis analysis and intervention at appropriate times. Currently, the judgment of dangerous online public opinion relies on only a few simple statistical metrics, such as the number of reads, comments, and likes, without considering the dissemination strength, dissemination mechanisms, and target user groups of different platforms. This can easily lead to misjudgments, resulting in overreactions or delays, and failing to effectively control the spread of dangerous public opinion. Summary of the Invention

[0004] Based on this, it is necessary to propose an analysis module and method for the ecological environment public opinion monitoring system of the smart environmental protection platform to address the above problems.

[0005] An analytical method for an intelligent environmental protection platform's ecological environment public opinion monitoring system includes:

[0006] Obtain the user's selected information topic creation instruction, create an information public opinion topic according to the information topic creation instruction, the information topic instruction includes information source and / or information search conditions, and collect public opinion information to be analyzed according to the information topic instruction;

[0007] Target public opinion information is obtained from the public opinion information to be analyzed based on the keywords or sample articles corresponding to the target environmental event.

[0008] The target public opinion information is analyzed to obtain the event level and attention level of the environmental event corresponding to the environmental event setting information, and an environmental event report is generated.

[0009] The step of analyzing the target public opinion information, obtaining the event level and attention level of the environmental event corresponding to the environmental event setting information, and generating an environmental event report includes:

[0010] Automatic and intelligent analysis of target public opinion information on the environmental event from at least one dimension, including time, region, and website;

[0011] The system automatically and intelligently analyzes the participation of netizens in the environmental protection event from at least one dimension, including netizen distribution, age, gender, and participation method, to obtain a user profile of the netizens.

[0012] Based on the target public opinion information, an event development trend diagram is obtained, which includes at least one key node of the event.

[0013] Conduct a positive and negative stance analysis of media reports and netizens' opinions on the aforementioned environmental incident, and obtain the results of the stance analysis;

[0014] The environmental event report is generated based on the described population profile, the schematic diagram of the event's development trend, and the results of the position analysis.

[0015] The step of analyzing the positive and negative stances of media reports and netizens regarding the environmental incident includes:

[0016] The analysis of environmental public opinion comments aims to extract sentiment words, quickly calculate the sentiment word tendencies and their degree, and obtain the public's attitudes and opinions towards environmental policy decisions.

[0017] The steps of analyzing comments in environmental public opinion, extracting sentiment words, and quickly calculating the sentiment word tendency and degree include:

[0018] The target public opinion information is analyzed for sentiment tendency based on preset word tendencies. The preset word tendencies include nouns, verbs, adjectives, and adverbs and their tendencies, as well as personal names, organization names, product names, event names and their tendencies.

[0019] Subjective information in sentences of the target public opinion information is analyzed and extracted, the sentiment tendency of the sentences is judged, and elements related to the sentiment tendency are extracted from the sentences. The elements include the holder of the sentiment tendency, the evaluation object, the polarity of the tendency, and the intensity.

[0020] To determine the overall sentiment of the articles containing the target public opinion information.

[0021] The step of obtaining a schematic diagram of the event development trend based on the target public opinion information includes:

[0022] The analysis is based on changes in webpage data, word frequency, reposting, and dissemination in the public opinion information to be analyzed, to obtain trend predictions of the evolution of environmental public opinion, and to visualize the initiation and development process of the public opinion information to be analyzed in a spatiotemporal manner.

[0023] The step of analyzing changes in webpage data, word frequency, reposting, and dissemination within the public opinion information to be analyzed includes:

[0024] Based on natural language processing technology, all websites disseminating the same public opinion content are identified according to the similarity of article content.

[0025] Based on changes in webpage data, word frequency, reposting, and dissemination on the aforementioned dissemination websites, the analysis of public opinion dissemination trends is obtained and presented in different categories.

[0026] The step of automatically and intelligently analyzing the online participation in the environmental event from at least one dimension, including online user distribution, age, gender, and participation method, to obtain a user profile, includes:

[0027] The public behavior in the public opinion information to be analyzed is analyzed and mined to extract users' interest characteristics and focus, and spatial analysis methods are combined to extract the spatial areas that users are interested in.

[0028] The steps of analyzing and mining public behavior in the public opinion information to be analyzed, extracting users' interest characteristics and focus, and extracting spatial areas of interest to users using spatial analysis methods include:

[0029] Based on a multi-dimensional context-aware computing model, the basic context information of users is determined, and users are further classified and summarized into a set of basic user types with spatiotemporal characteristics and focus of attention.

[0030] Automatically label user contextual information and extract user interest feature data;

[0031] By spatially labeling the user's areas of interest and combining this with an analysis of the connections between the surrounding environmental pollution sources and ecologically sensitive areas, the range of spatial areas that the user is interested in can be determined.

[0032] The steps of determining the user's basic contextual information based on the multidimensional context-aware computing model, refining user classification, and summarizing a set of basic user types with spatiotemporal characteristics and focus areas include:

[0033] A multi-dimensional PDA emotion model is established, where P represents pleasure, indicating the positive or negative characteristics of an individual's emotional state; A represents activation, indicating the individual's neurophysiological activation level; and D represents dominance, indicating the individual's influence on or being influenced by the situation and others.

[0034] The sentiment computing database is divided into a text database and an icon database according to its form. The text database is divided into two categories: positive and negative, and five sentiment categories: strong positive, weak positive, neutral, weak negative, and strong negative. The icon database includes a variety of commonly used icons, each of which is assigned a different emotion to obtain the emotional expression in the current discourse.

[0035] The emotional texts or icons corresponding to the text database and the icon database are all assigned different scores of P-value and A-value.

[0036] To obtain the final P-value and A-value, the D-value needs to be associated with spatial annotations and used as the coefficient of the function corresponding to the P-value and A-value. The D-value is set to be between 0.1 and 2. The P-value is labeled based on user behavior or labeled by the user.

[0037] The step of collecting public opinion information to be analyzed according to the information topic instruction includes:

[0038] The weight of each piece of public opinion information to be analyzed is calculated by taking into account the importance of the website, the position of the article, the relevance of the topic, the number of clicks and replies, the amount of dissemination, and user-defined rules. Hot public opinion information is obtained from the public opinion information to be analyzed, and industry hot information and regional hot information are customized based on the hot public opinion information.

[0039] The step of collecting public opinion information to be analyzed according to the information topic instruction includes:

[0040] Analyze the relevance of the aforementioned hot public opinion information to environmental protection departments, identify the relevant environmental protection departments, provide corresponding solutions for the aforementioned hot public opinion information, and promptly disclose the progress of handling ecological public opinion events;

[0041] Analyze the relevance of the aforementioned trending public opinion information to the enterprises, identify the relevant enterprises, and urge the enterprises to promptly disclose the handling and progress of the incidents to the public;

[0042] Based on the user preference analysis results of public behavior characteristics, the relevance of the hot public opinion information is analyzed, and personalized information is quickly pushed to the public.

[0043] The step of collecting public opinion information to be analyzed according to the information topic instruction includes:

[0044] The system performs correlation analysis on at least one of the factors involved in the hot public opinion information, such as names of people, place names, content, and people, to form corresponding related information content, and then classifies, manages, and displays the related information content.

[0045] An analysis module of an intelligent environmental protection platform's ecological environment public opinion monitoring system includes:

[0046] The collection unit is used to acquire the information topic instructions selected by the user, the information topic instructions including information sources and / or information search conditions, and to collect public opinion information to be analyzed according to the information topic instructions.

[0047] The acquisition unit is used to acquire target public opinion information from the public opinion information to be analyzed based on the keywords or sample articles corresponding to the target environmental event.

[0048] The analysis unit is used to analyze the target public opinion information, obtain the event level and attention level of the environmental event corresponding to the environmental event setting information, and generate an environmental event report.

[0049] An analysis module of an intelligent environmental protection platform ecological environment public opinion monitoring system includes a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method described above.

[0050] The management and emergency module of the drinking water source management system based on the smart environmental protection platform includes a storage medium that stores a computer program. When the computer program is executed by a processor, the processor performs the steps of the method described above.

[0051] The embodiments of the present invention have the following beneficial effects:

[0052] The system obtains the user's selected information topic creation instructions, collects the public opinion information to be analyzed according to the instructions, extracts the target public opinion information from the public opinion information to be analyzed based on the keywords or sample articles corresponding to the target environmental event, analyzes the target public opinion information, obtains the event level and attention level of the environmental event corresponding to the set information, and generates an environmental event report. This allows users to understand public opinion information in a timely manner, analyze it promptly, and obtain environmental event reports, thereby improving user work efficiency and reducing workload. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] in:

[0055] Figure 1 This is a flowchart illustrating the first embodiment of the analysis method of the intelligent environmental protection platform ecological environment public opinion monitoring system provided by the present invention;

[0056] Figure 2 This is a schematic diagram of the environmental incident reporting page provided by the present invention;

[0057] Figure 3 This is a flowchart illustrating the second embodiment of the analysis method of the intelligent environmental protection platform ecological environment public opinion monitoring system provided by the present invention;

[0058] Figure 4 This is a schematic diagram of a page showing the amount of coverage on key websites, provided by the present invention.

[0059] Figure 5 This is a schematic diagram of the position analysis results provided by the present invention.

[0060] Figure 6 This is a flowchart illustrating the third embodiment of the analysis method for the intelligent environmental protection platform ecological environment public opinion monitoring system provided by the present invention;

[0061] Figure 7 This is a schematic diagram of a snapshot page provided by the present invention;

[0062] Figure 8 This is a schematic diagram of the structure of an embodiment of the analysis module of the intelligent environmental protection platform ecological environment public opinion monitoring system provided by the present invention;

[0063] Figure 9 This is a schematic diagram of another embodiment of the analysis module of the intelligent environmental protection platform ecological environment public opinion monitoring system provided by the present invention;

[0064] Figure 10 This is a schematic diagram of an embodiment of the storage medium provided by the present invention. Detailed Implementation

[0065] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0066] Please see Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the analysis method for the intelligent environmental protection platform's ecological environment public opinion monitoring system provided by the present invention. The intelligent environmental protection platform's ecological environment public opinion monitoring system provided by the present invention includes the following steps:

[0067] S101: Obtain the user-selected information topic creation instruction, create an information public opinion topic according to the information topic creation instruction, the information topic instruction includes information source and / or information search conditions, and collect public opinion information to be analyzed according to the information topic instruction.

[0068] In a specific implementation scenario, the user selects an information topic instruction. The information topic instruction is used to construct at least one information topic, including information source and / or information search conditions. The information source indicates where to obtain the public opinion information to be analyzed, such as Weibo, specific websites, Tieba, public accounts, etc. The information search conditions include at least one of the following: search area, search industry, search keywords, search validity period, and search frequency.

[0069] Furthermore, the information topic instructions also include topic groups, including at least one of the following: publicity topics, public opinion topics, key focus topics, historical topics, and report topics, as well as the audience that can access the search results and the topic level (levels 1-5 + special level).

[0070] Once an information and public opinion topic is established, it will continuously collect information from designated sources that meets the search criteria, gather information to be analyzed, and then organize and report it to users. Users can also choose any established information and public opinion topic to view the collected information to be analyzed.

[0071] In one implementation scenario, to quickly and accurately extract valuable clues from web page information, the system uses entity extraction technology to extract meaningful information such as names of people, places, times, locations, organization names, and proper nouns from public opinion information and store them in the database, thereby providing data support for the subsequent analysis and judgment of public opinion information.

[0072] S102: Obtain target public opinion information from the public opinion information to be analyzed based on the keywords or sample articles corresponding to the target environmental event.

[0073] In a specific implementation scenario, target public opinion information is obtained from the public opinion information to be analyzed based on keywords or sample articles corresponding to the target environmental event. The target environmental event setting information is edited by the user based on key or trending environmental events, including corresponding keywords or sample articles. For example, if a Weibo post is widely shared online, including by influential figures, that Weibo post is used as a sample article. Alternatively, keywords can be obtained based on the content of key or trending environmental events, such as location, people, and events, for example, water pollution, sewage treatment, tap water odor, Bao'an District, Xin'an Street, staff, receptionist, etc.

[0074] Target public opinion information can be extracted from the public opinion information to be analyzed based on keywords or sample articles. For example, target public opinion information containing keywords can be filtered out from the public opinion information to be analyzed. Another example is to perform semantic analysis based on sample articles to extract target public opinion information with the same or similar semantic information from the public opinion information to be analyzed. Alternatively, information describing events and biased statements can be extracted from sample articles to extract target public opinion information describing the same events and having the same bias from the public opinion information to be analyzed.

[0075] S103: Analyze the target public opinion information, obtain the event level and attention level of the environmental event corresponding to the environmental event setting information, and generate an environmental event report.

[0076] In a specific implementation scenario, the target public opinion information is analyzed to obtain the event level and attention level of the environmental event corresponding to the set information, and an environmental event report is generated. The attention level can be obtained based on the number of comments, reposts, and the overall data volume of the target public opinion information; the event level can be obtained based on the specific content of the environmental event, its scope of impact, and the speed of its spread. The environmental event report is generated by combining the event level and attention level with an overview of the target public opinion information. The overview of the target public opinion information includes at least one of the following: the timeframe of attention to the environmental event, the location scope, the event content, and the individuals or entities involved. Furthermore, a timeline can be used to display the trend of the target public opinion information's popularity. Please refer to [reference needed]. Figure 2 , Figure 2 This is a schematic diagram of the environmental incident reporting page provided by the present invention.

[0077] In other implementation scenarios, it can acquire users' key areas of interest and key information, and automatically classify massive amounts of target public opinion information, such as classifying them according to water pollution, air pollution, or soil pollution. In other implementation scenarios, it can perform semantic analysis on each article in the target public opinion information, group documents with similar content into one category, and automatically generate keywords for that category. The classification can be continuously optimized through machine learning and supports multi-dimensional classification.

[0078] In other implementation scenarios, users obtain a list of environmental events, which is categorized based on target public opinion information. These events are then further classified and tiered for display. Users can view all related reports for each environmental event and sort and filter them by time, popularity, and whether they are positive or negative. Users can perform operations on related reports, including tagging, adding to favorites, sending articles, and batch exporting. This allows users to more conveniently obtain analysis results for environmental events, improving their work efficiency.

[0079] In one implementation scenario, users can search for articles in target public opinion information by entering keywords or phrases, and the search results are returned to the user based on relevance.

[0080] In one implementation scenario, when a user browses target public opinion information, the system retrieves the user's snapshot command and automatically crawls the original article page (including images and text) via the original article link. The server-side limit for saving snapshots is 100 per client organization. If the limit is exceeded, the system displays the message: "You cannot save more than 100 snapshots. Please delete some snapshots and try again." Please refer to [the relevant documentation / reference]. Figure 7 , Figure 7 This is a schematic diagram of a snapshot page provided by the present invention. Newly generated snapshots have a caption at the top stating something like "The following is a snapshot of this webpage taken at 19:44:58 Beijing time on August 5, 2018" and "The author of the webpage http: / / www.nihaowang.com / is not responsible for its content. Snapshots do not represent the real-time page of the searched website." The newly generated snapshot link is generated by the AMS system and is valid indefinitely. If the snapshot name is not filled in, the default name is "2018-08-05-19:44:58-Zhang San," where Zhang San is the name of the client or content creator logging into the system. Snapshots can be edited, deleted, viewed, and saved.

[0081] As described above, in this embodiment, the user selects an information topic creation instruction, collects public opinion information to be analyzed according to the information topic instruction, obtains target public opinion information from the public opinion information to be analyzed based on the keywords or sample articles corresponding to the target environmental event setting information, analyzes the target public opinion information, obtains the event level and attention level of the environmental event corresponding to the environmental event setting information, and generates an environmental event report. This allows users to understand public opinion information in a timely manner, analyze it promptly, and obtain environmental event reports, thereby improving user work efficiency and reducing workload.

[0082] Please see Figure 3 , Figure 3 This is a flowchart illustrating the second embodiment of the analysis method for the intelligent environmental protection platform's ecological environment public opinion monitoring system provided by the present invention. The intelligent environmental protection platform's ecological environment public opinion monitoring system provided by the present invention includes the following steps:

[0083] S201: Obtain the user-selected information topic creation instruction, create an information public opinion topic according to the information topic creation instruction, the information topic instruction includes information source and / or information search conditions, and collect public opinion information to be analyzed according to the information topic instruction.

[0084] S202: Obtain target public opinion information from the public opinion information to be analyzed based on the keywords or sample articles corresponding to the target environmental event.

[0085] In a specific implementation scenario, steps S201-S202 are basically the same as steps S101-S102 in the first embodiment of the analysis method of the intelligent environmental protection platform ecological environment public opinion monitoring system provided by the present invention, and will not be described again here.

[0086] S203: Automated intelligent analysis of public opinion regarding environmental events from at least one dimension, including time, region, and website.

[0087] In a specific implementation scenario, the system automatically and intelligently analyzes media coverage of an environmental event from multiple dimensions, including time, region, and website. Key events can be displayed through time nodes. For example, it can acquire the public opinion trend (positive or negative), popularity, and public attention at different points in time. It can collect target public opinion information at points where the trend changes (e.g., from positive to negative) or popularity surges, and analyze this information to identify key events, such as timely statements, mitigation measures, or compensation measures. Furthermore, it can display the coverage volume on key websites, selected based on daily traffic or user settings. It can also show the geographical and regional distribution of coverage, allowing users to better understand the distribution of public opinion. Please refer to the following references. Figure 4 , Figure 4 This is a schematic diagram of a page showing the amount of news coverage on key websites, provided by the present invention.

[0088] S204: Automated intelligent analysis of netizens' participation in environmental events from at least one dimension, including netizen distribution, age, gender, and participation method, to obtain a user profile.

[0089] In a specific implementation scenario, automated intelligent analysis is performed on netizens (including those who forward, post, comment, like, and save) related to the target public opinion information, considering at least one dimension: regional distribution, age, gender, and participation method. This analysis aims to obtain the participation trend of netizens throughout the entire event cycle of the environmental event, such as the changing trend of the number of participants in the early and middle stages of the event. It also aims to obtain information on the active participation of netizens in the environmental event, such as whether there are more people forwarding in support or expressing protest and dissatisfaction. Finally, it aims to obtain a demographic profile of the netizens participating in the environmental event, including age, gender, participation method, verification status, sentiment, level of participation, and duration of attention.

[0090] In one implementation scenario, public behavior within target public opinion information can be analyzed and mined to extract user interest characteristics and key concerns. Spatial analysis methods can then be used to extract spatial regions of interest to users. Based on a multi-dimensional context-aware computing model, basic contextual information of public users is determined, and users are further categorized to summarize a set of basic user types with spatiotemporal characteristics and key concerns. Semi-automatic annotation of user contextual information can be performed to extract user interest feature data. This data is then described and expressed using web semantic technology to obtain user interest characteristics. By spatially annotating user interest regions and combining this with correlation analysis with surrounding environmental pollution sources and ecologically sensitive areas, the spatial range of user attention can be analyzed, providing support for subsequent precise and personalized information delivery.

[0091] In one implementation scenario, a PDA multi-dimensional sentiment model is established, where P represents pleasure level, indicating the positive or negative characteristics of an individual's emotional state; A represents activation level, indicating the individual's neurophysiological activation level; and D represents dominance level, indicating the individual's influence or being influenced by the situation and others. Sentiment mining is performed on the public opinion information to be analyzed based on the PDA multi-dimensional sentiment model. A pre-set database for sentiment calculation of the PDA multi-dimensional sentiment model is used, including a text database and an icon database. The public opinion information to be analyzed also includes text and image information. Sentiment mining from both text and image perspectives allows for more accurate identification of users' sentiment tendencies. The text database is divided into five sentiment categories: strongly positive, weakly positive, neutral, weakly negative, and strongly negative. The icon database includes various commonly used icons, each assigned a different emotional level. The emotional text in the text database and the icons in the icon database are assigned different P and A scores, and the A and P values ​​corresponding to the emotional text and icons are continuously adjusted through deep learning or self-learning. Based on the PDA multi-dimensional sentiment model, the public opinion information to be analyzed is used to obtain the final P-value and A-value. The D-value, as the coefficient of the function corresponding to the P-value and A-value, needs to be spatially labeled and set between 0.1 and 2. The P-value is labeled based on user behavior or labeled by the user themselves. Based on the final A-value, P-value, and D-value, the user's basic contextual information is determined.

[0092] S205: Obtain a schematic diagram of the event's development trend based on the target public opinion information. The schematic diagram of the event's development trend includes at least one key node of the event.

[0093] In a specific implementation scenario, this involves analyzing the dissemination and evolution of an environmental event throughout its entire lifecycle based on target public opinion information. Key milestones are extracted from relevant news reports, and a timeline is drawn to visually illustrate the event's origins, development, and evolution.

[0094] In one implementation scenario, by acquiring changes in webpage data, word frequency, reposting, and dissemination based on target public opinion information, the system can predict the trend of environmental public opinion evolution and provide spatiotemporal visualization of the initiation and development process of public opinion. Based on natural language processing technology, it can calculate similar articles according to content similarity, facilitating the acquisition of all websites disseminating the same content. It can analyze and display the trend of public opinion information over a period of time, categorizing it across different platforms such as forums and news. Furthermore, it can analyze and track important trending news information, automatically compiling statistics on related news and forum dissemination and public opinion trends, and conducting outbreak trend analysis.

[0095] S206: Conduct media reports on environmental events and analyze the positive and negative stances of netizens to obtain the results of the stance analysis.

[0096] In a specific implementation scenario, data on media reports and online opinions regarding environmental events (positive and negative stances) are collected, statistically analyzed, and the results of the stance analysis are obtained. Please refer to the following: Figure 5 , Figure 5 This is a schematic diagram of the position analysis results provided by the present invention.

[0097] In one implementation scenario, a sentiment lexicon with specific biases can be established based on machine learning and manual training. Sentiment analysis is then performed on target public opinion information based on this lexicon, analyzing comments (such as message boards and news comments), extracting sentiment words from these comments, and using neural networks to quickly calculate the bias and degree of these sentiment words, thereby obtaining the public's attitudes and opinions towards environmental protection decisions. Furthermore, target public opinion information can be differentiated into positive, negative, and neutral categories, allowing for timely analysis and countermeasures to prevent the spread of negative sentiment.

[0098] In an implementation scenario, the positive or negative connotation (or polarity) of words is typically categorized into three types: positive, negative, and neutral. Besides polarity, the sentiment tendency of words also includes the intensity of that tendency. Sentiment tendency analysis is performed on the words in the target public opinion information based on preset word tendencies in a sentiment lexicon. These preset tendencies include nouns, verbs, adjectives, and adverbs and their tendencies, as well as names of people, organizations, products, and events and their tendencies. Statistical analysis is then performed on the tendencies of each word in the target public opinion information to obtain the sentiment tendency and its intensity.

[0099] In one implementation scenario, subjective information in sentences of target public opinion information is analyzed and extracted, the sentiment tendency of sentences is judged, and elements related to the sentiment tendency discourse are extracted from sentences. These elements include the holder of the sentiment tendency discourse, the evaluation object, the polarity of the tendency, and the intensity, thereby obtaining the sentiment word tendency and degree of tendency of each sentence, and thus obtaining the sentiment word tendency and degree of tendency of the target public opinion information.

[0100] In one implementation scenario, the overall sentiment of each article in the target public opinion information is judged, that is, the positive or negative attitude, so as to obtain the sentiment word tendency and degree of tendency of the target public opinion information.

[0101] In one implementation scenario, target public opinion information is extracted from different information sources, and sentiment information on a specific topic is integrated and analyzed to uncover the characteristics and trends of users' overall attitudes toward the environmental event.

[0102] S207: Generate an environmental incident report based on the crowd profile, the schematic diagram of the event's development trend, and the results of the position analysis.

[0103] In a specific implementation scenario, an environmental incident report is generated based on the demographic profile, a schematic diagram of the event's development trend, and the results of the position analysis.

[0104] As described above, this implementation scenario automatically and intelligently analyzes public opinion regarding environmental events from at least one dimension (time, region, website) and automatically and intelligently analyzes public participation in environmental events from at least one dimension (distribution of netizens, age, gender, participation method). It obtains a profile of netizens, generates a trend diagram of event development based on the target public opinion information, analyzes media reports and netizens' positive and negative stances on environmental events, obtains stance analysis results, and generates an environmental event report based on the user profile, the trend diagram of event development, and the stance analysis results. Users can obtain comprehensive and accurate analysis results of public opinion information, improving the effectiveness and accuracy of the analysis.

[0105] Please see Figure 6 , Figure 6 This is a flowchart illustrating the third embodiment of the analysis method for the intelligent environmental protection platform's ecological environment public opinion monitoring system provided by the present invention. The intelligent environmental protection platform's ecological environment public opinion monitoring system provided by the present invention includes the following steps:

[0106] S301: Obtain the user-selected information topic creation instruction, create an information public opinion topic according to the information topic creation instruction, the information topic instruction includes information source and / or information search conditions, and collect public opinion information to be analyzed according to the information topic instruction.

[0107] In a specific implementation scenario, step S301 is basically the same as step S101 in the first embodiment of the analysis method of the smart environmental protection platform ecological environment public opinion monitoring system provided by the present invention, and will not be described again here.

[0108] S302: Calculate the weight of each piece of public opinion information to be analyzed by taking into account the importance of the website, the position of the article, the relevance of the topic, the number of clicks and replies, the amount of dissemination, and user-defined rules. Obtain the hot public opinion information in the public opinion information to be analyzed, and customize industry hot information and regional hot information based on the hot public opinion information.

[0109] In a specific implementation scenario, complex parameters such as website importance, article location, topic relevance, number of clicks and replies, dissemination volume, and user-defined rules can be comprehensively considered to calculate the weight of public opinion information and accurately analyze trending public opinion information.

[0110] By statistically analyzing trending information among internet users, the system enables the analysis and tracking of emerging information trends online. It can acquire user visit data for specific websites, extract and process information from those websites, and automatically identify trending topics based on user activity. For the environmental protection industry and specific regions, the system can be customized to provide detailed industry-specific and regional trending information.

[0111] It analyzes and tracks important environmental news and information, and can promptly grasp the outbreak points and developments of online public opinion caused by environmental pollution incidents. It automatically tracks and statistically analyzes the number of news articles and their dissemination chains across various websites and communities, providing trending news for different time periods. For each trending news item, users can also view its related dissemination chain to understand the number of times the news was disseminated on which sites within a specific timeframe.

[0112] In other implementation scenarios, hot keywords can be used to effectively link different information, including the correlation analysis of factors such as names of people and places involved in hot public opinion information, the correlation analysis of similar articles, and the analysis of related figures, thereby forming corresponding related information content. The related information can be classified, managed and displayed, thus providing support for high-end retrieval of hot keywords and diversified information display, while improving the efficiency of users in obtaining hot information.

[0113] Based on clustering analysis algorithms, it can accurately analyze similar articles related to the same topic and autonomously discover the same target figures appearing in different articles, thus providing effective location assistance for public opinion analysis and handling.

[0114] In one implementation scenario, the system can predict the public opinion information that a user is interested in based on their reading and search history. It can also calculate the public opinion information that the user is interested in based on content recommendation algorithms and collaborative recommendation algorithms. Finally, it can push the public opinion information that the user is interested in to ecological and environmental supervision apps, enterprise apps, and citizen apps based on mobile APP technology, so as to realize the proactive recommendation of public opinion to ecological and environmental supervision departments, enterprises, and the public on demand.

[0115] This system analyzes the relevance of trending public opinion information to environmental protection departments. When environmental public opinion events occur, it quickly locates the relevant departments, verifies the events, provides corresponding solutions for specific problems, and promptly discloses the progress of handling ecological public opinion events to guide public opinion. Based on key information from trending public opinion (such as business keywords and related phrases), it intelligently matches and locates relevant business departments. It maps and matches the environmental public opinion event information corresponding to the trending public opinion information with the public opinion emergency response plan on the server, and determines the methods for the business departments to correctly handle public opinion based on the matching degree. According to the real-time changes in public opinion on environmental events and the characteristics of public user behavior, it designs authoritative and scientifically sound positive environmental event handling plans. Supported by a mobile APP, it accurately pushes the correct handling methods to environmental protection department users according to the progress of environmental public opinion event handling, thereby guiding public opinion on environmental events.

[0116] Based on the intelligent matching of key information from trending public opinion, relevant enterprises are identified. This involves mapping and matching environmental public opinion events corresponding to trending topics with emergency response plans stored on a server. The matching degree determines the appropriate methods for enterprises to handle public opinion events. According to the real-time changes in environmental public opinion and the characteristics of public user behavior, authoritative and scientifically sound positive environmental event handling plans are designed. Supported by a mobile app platform, these plans are precisely pushed to enterprise users based on the progress of environmental public opinion event handling, thereby guiding public opinion on environmental events.

[0117] By analyzing user preferences based on public behavior characteristics, and leveraging a mobile app platform, the relevance of environmental hot topics is analyzed. When environmental public opinion events occur, personalized information is quickly pushed to the public to guide public opinion. Based on the public user preferences analyzed from public behavior characteristics, user information needs are mapped and matched with ecological information on the server. Environmental information data that meets user preferences is obtained based on the matching degree. According to the real-time changes in environmental public opinion and the characteristics of public user behavior, authoritative and scientifically sound positive environmental event information is designed and precisely pushed to the public using a mobile app platform to guide public opinion on environmental events.

[0118] As described above, this embodiment comprehensively considers factors such as website importance, article location, topic relevance, number of clicks and replies, dissemination volume, and user-defined rules to calculate the weight of each piece of public opinion information to be analyzed. It then obtains hot public opinion information from the information to be analyzed and customizes industry hot information and regional hot information based on this information. This allows for the automatic and timely acquisition and analysis of hot public opinion information, effectively improving user work efficiency and reducing workload.

[0119] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of an embodiment of the analysis module of the intelligent environmental protection platform ecological environment public opinion monitoring system provided by the present invention. The analysis module 10 of the intelligent environmental protection platform ecological environment public opinion monitoring system includes: a collection unit 11, an acquisition unit 12, and an analysis unit 13.

[0120] The collection unit 11 is used to acquire the information topic instructions selected by the user. The information topic instructions include information sources and / or information search conditions, and collect the public opinion information to be analyzed according to the information topic instructions. The acquisition unit 12 is used to acquire the target public opinion information from the public opinion information to be analyzed based on the keywords or sample articles corresponding to the target environmental event. The analysis unit 13 is used to analyze the target public opinion information, acquire the event level and attention level of the environmental event corresponding to the environmental event setting information, and generate an environmental event report.

[0121] Analysis unit 13 is also used to automatically and intelligently analyze the target public opinion information of environmental events from at least one dimension, including time, region, and website; to automatically and intelligently analyze the participation of netizens in environmental events from at least one dimension, including netizen distribution, age, gender, and participation method, and obtain a netizen profile; to obtain a schematic diagram of the event development trend based on the target public opinion information, which includes at least one key node of the event; to conduct media reports on environmental events and positive and negative positions of netizens' opinions, and obtain position analysis results; and to generate an environmental event report based on the netizen profile, the schematic diagram of the event development trend, and the position analysis results.

[0122] Analysis unit 13 is also used to analyze the comments in environmental public opinion, extract sentiment words, quickly calculate the sentiment word tendencies and tendencies, and obtain the public's attitudes and opinions on environmental policy decisions.

[0123] Analysis unit 13 is also used to perform sentiment analysis on the words in the target public opinion information based on preset word tendencies. The preset word tendencies include nouns, verbs, adjectives, and adverbs and their tendencies, as well as personal names, organization names, product names, event names and their tendencies; analyze and extract subjective information in the sentences of the target public opinion information, judge the sentiment tendency of the sentences, and extract elements related to the sentiment tendency argument from the sentences. The elements include the holder of the sentiment tendency argument, the evaluation object, the polarity of the tendency, and the intensity; and judge the sentiment tendency of the target public opinion information article as a whole.

[0124] The analysis unit 13 is also used to analyze the changes in web page data, word frequency, reposting and dissemination in the public opinion information to be analyzed, obtain the trend prediction of the evolution of environmental public opinion, and visualize the initiation and development process of the public opinion information to be analyzed in time and space.

[0125] Analysis unit 13 is also used to obtain all dissemination websites containing the same public opinion content based on the similarity of article content using natural language processing technology; and to obtain public opinion dissemination trend analysis based on changes in web page data, word frequency, reprinting and diffusion of dissemination websites, and present the analysis in different categories.

[0126] Analysis unit 13 is also used to analyze and mine public behavior in the public opinion information to be analyzed, extract users' interest characteristics and focus, and extract spatial areas of interest to users by combining spatial analysis methods.

[0127] Analysis unit 13 is also used to determine the user's basic context information based on a multi-dimensional context-aware computing model, and to further classify the user and summarize the basic user type set with spatiotemporal characteristics and focus of attention; to automatically label the user's context information and extract the user's interest feature data; to spatially label the user's interest area and, in conjunction with the surrounding environmental pollution sources and ecologically sensitive areas, to analyze the spatial area range of the user's attention.

[0128] The collection unit 11 is also used to comprehensively consider the importance of the website, the position of the article, the relevance of the topic, the number of clicks and replies, the amount of dissemination, and user-defined rules to calculate the weight of each piece of public opinion information to be analyzed, obtain the hot public opinion information in the public opinion information to be analyzed, and customize industry hot information and regional hot information based on the hot public opinion information.

[0129] The collection unit 11 is also used to analyze the relevance of hot public opinion information to environmental protection departments, locate relevant environmental protection departments, provide corresponding solutions for hot public opinion information, and promptly disclose the handling process of ecological public opinion events; analyze the relevance of hot public opinion information to enterprises, locate relevant enterprises, and urge enterprises to quickly disclose the handling and progress of events to the public; and analyze the relevance of hot public opinion information based on the user preference analysis results of public behavior characteristics, and quickly push personalized information to the public.

[0130] The collection unit 11 is also used to perform correlation analysis on at least one of the factors among the names of people, places, content, and people involved in the hot public opinion information, form corresponding information association content, and classify, manage and display the information association content.

[0131] The collection unit 11 is also used to obtain the search information input by the user and display the searched public opinion information from the public opinion information to be analyzed based on the search information.

[0132] Please see Figure 9 , Figure 9 This is a schematic diagram of another embodiment of the analysis module of the intelligent environmental protection platform's ecological environment public opinion monitoring system provided by the present invention. The analysis module 20 of the intelligent environmental protection platform's ecological environment public opinion monitoring system includes a processor 21 and a memory 22. The processor 21 is coupled to the memory 22. The memory 22 stores a computer program, which the processor 21 executes during operation to achieve the following: Figure 1 , Figure 3 , Figure 6 The method is shown above. For detailed instructions, please refer to the above; they will not be repeated here.

[0133] Please see Figure 10 , Figure 10 This is a schematic diagram of an embodiment of the storage medium provided by the present invention. The readable storage medium 30 stores at least one computer program 31, which is executed by a processor to perform, as described above. Figure 1 , Figure 3 , Figure 6 The method shown is detailed above and will not be repeated here. In one embodiment, the storage medium 30 can be a storage chip in the terminal, a hard disk, a portable hard disk, a USB flash drive, an optical disc, or other read / write storage devices, or even a server, etc.

[0134] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0135] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0136] The above embodiments merely illustrate several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. An analysis method of an ecological environment public opinion monitoring system of a smart environmental protection platform, characterized in that, include: Obtain the user's selected information topic creation instruction, create an information public opinion topic according to the information topic creation instruction, the information topic instruction includes information source and / or information search conditions, and collect public opinion information to be analyzed according to the information topic instruction; Target public opinion information is obtained from the public opinion information to be analyzed based on the keywords or sample articles corresponding to the target environmental event. The target public opinion information is analyzed to obtain the event level and attention level of the environmental event corresponding to the environmental event setting information, and an environmental event report is generated. The step of analyzing the target public opinion information, obtaining the event level and attention level of the environmental event corresponding to the environmental event setting information, and generating an environmental event report includes: Automatic and intelligent analysis of target public opinion information on the environmental event from at least one dimension, including time, region, and website; The system automatically and intelligently analyzes the participation of netizens in the environmental protection event from at least one dimension, including netizen distribution, age, gender, and participation method, to obtain a user profile of the netizens. Based on the target public opinion information, an event development trend diagram is obtained, which includes at least one key node of the event. Conduct a positive and negative stance analysis of media reports and netizens' opinions on the aforementioned environmental incident, and obtain the results of the stance analysis; The environmental incident report is generated based on the described demographic profile, the schematic diagram of the event's development trend, and the results of the position analysis. The step of automatically and intelligently analyzing the online participation in the environmental event from at least one dimension, including online user distribution, age, gender, and participation method, to obtain a user profile, includes: The public behavior in the public opinion information to be analyzed is analyzed and mined to extract users' interest characteristics and focus, and spatial analysis methods are combined to extract the spatial areas that users are interested in. The steps of analyzing and mining public behavior in the public opinion information to be analyzed, extracting users' interest characteristics and focus, and extracting spatial areas of interest to users using spatial analysis methods include: Based on a multi-dimensional context-aware computing model, the basic context information of users is determined, and users are further classified and summarized into a set of basic user types with spatiotemporal characteristics and focus of attention. Automatically label user contextual information and extract user interest feature data; Spatial labeling of user interest areas, combined with analysis of connections with surrounding environmental pollution sources and ecologically sensitive areas, reveals the range of spatial areas that users are interested in. The steps for determining the user's basic contextual information based on the multidimensional context-aware computing model include: Establish a PDA multidimensional emotion model, where P represents pleasure, used to represent the positive and negative characteristics of an individual's emotional state, A represents activation, used to represent an individual's neurophysiological activation level, and D represents dominance, used to represent an individual's influence on or being influenced by the situation and others. The sentiment computing database is divided into a text database and an icon database according to its form. The text database is divided into five sentiment categories, namely strong positive, weak positive, neutral, weak negative, and strong negative. The icon database includes a variety of commonly used icons, each of which is assigned a different level of emotion. The sentiment text in the text database and the icons in the icon database are assigned different scores of P-value and A-value. The PDA multi-dimensional sentiment model is used to analyze the public opinion information to be analyzed, and the final P value and A value are obtained. The D value, as the coefficient of the function corresponding to the P value and A value, needs to be associated with spatial labeling and set between 0.1 and 2. The P value is labeled according to user behavior or labeled by the user himself. The user's basic contextual information is determined based on the final A, P, and D values. 2.The analysis method of the eco-environment public opinion monitoring system of the smart environmental protection platform according to claim 1, characterized in that, The steps for analyzing the positive and negative stances of media reports and online opinions regarding the environmental incident include: The analysis of environmental public opinion comments aims to extract sentiment words, quickly calculate the sentiment word tendencies and their degree, and obtain the public's attitudes and opinions towards environmental policy decisions.

3. The analysis method of the intelligent environmental protection platform ecological environment public opinion monitoring system according to claim 2, characterized in that, The steps involved in analyzing comments within environmental public opinion, extracting sentiment terms, and quickly calculating the sentiment tendency and degree of tendency of these terms include: The target public opinion information is analyzed for sentiment tendency based on preset word tendencies. The preset word tendencies include nouns, verbs, adjectives, and adverbs and their tendencies, as well as personal names, organization names, product names, event names and their tendencies. Subjective information in sentences of the target public opinion information is analyzed and extracted, the sentiment tendency of the sentences is judged, and elements related to the sentiment tendency are extracted from the sentences. The elements include the holder of the sentiment tendency, the evaluation object, the polarity of the tendency, and the intensity. To determine the overall sentiment of the articles containing the target public opinion information.

4. The analysis method of the intelligent environmental protection platform ecological environment public opinion monitoring system according to claim 1, characterized in that, The step of obtaining a schematic diagram of the event development trend based on the target public opinion information includes: The analysis is based on changes in webpage data, word frequency, reposting, and dissemination in the public opinion information to be analyzed, to obtain trend predictions of the evolution of environmental public opinion, and to visualize the initiation and development process of the public opinion information to be analyzed in a spatiotemporal manner.

5. The analysis method of the intelligent environmental protection platform ecological environment public opinion monitoring system according to claim 4, characterized in that, The step of analyzing the changes in webpage data, word frequency, reposting, and dissemination in the public opinion information to be analyzed includes: Based on natural language processing technology, all websites disseminating the same public opinion content are identified according to the similarity of article content. Based on changes in webpage data, word frequency, reposting, and dissemination on the aforementioned dissemination websites, the analysis of public opinion dissemination trends is obtained and presented in different categories.

6. The analysis method of the intelligent environmental protection platform ecological environment public opinion monitoring system according to claim 1, characterized in that, Following the step of collecting public opinion information to be analyzed according to the information topic instruction, the following steps are included: The weight of each piece of public opinion information to be analyzed is calculated by taking into account the importance of the website, the position of the article, the relevance of the topic, the number of clicks and replies, the amount of dissemination, and user-defined rules. Hot public opinion information is obtained from the public opinion information to be analyzed, and industry hot information and regional hot information are customized based on the hot public opinion information.

7. The analysis method of the intelligent environmental protection platform ecological environment public opinion monitoring system according to claim 6, characterized in that, Following the step of collecting public opinion information to be analyzed according to the information topic instruction, the following steps are included: Analyze the relevance of the aforementioned hot public opinion information to environmental protection departments, identify the relevant environmental protection departments, provide corresponding solutions for the aforementioned hot public opinion information, and promptly disclose the progress of handling ecological public opinion events; Analyze the relevance of the aforementioned trending public opinion information to the enterprises, identify the relevant enterprises, and urge the enterprises to promptly disclose the handling and progress of the incidents to the public; Based on the user preference analysis results of public behavior characteristics, the relevance of the hot public opinion information is analyzed, and personalized information is quickly pushed to the public.

8. The analysis method of the intelligent environmental protection platform ecological environment public opinion monitoring system according to claim 6, characterized in that, Following the step of collecting public opinion information to be analyzed according to the information topic instruction, the following steps are included: The system performs correlation analysis on at least one of the factors involved in the hot public opinion information, such as names of people, place names, content, and people, to form corresponding related information content, and then classifies, manages, and displays the related information content.

9. An analysis module of an intelligent environmental protection platform ecological environment public opinion monitoring system, characterized in that, include: The collection unit is used to obtain the information topic instructions selected by the user, the information topic instructions including information sources and / or information search conditions, and to collect public opinion information to be analyzed according to the information topic instructions. The acquisition unit is used to acquire target public opinion information from the public opinion information to be analyzed based on the keywords or sample articles corresponding to the target environmental event. The analysis unit is used to analyze the target public opinion information, obtain the event level and attention level of the environmental event corresponding to the environmental event setting information, and generate an environmental event report. The step of analyzing the target public opinion information, obtaining the event level and attention level of the environmental event corresponding to the environmental event setting information, and generating an environmental event report includes: Automatic and intelligent analysis of target public opinion information on the environmental event from at least one dimension, including time, region, and website; The system automatically and intelligently analyzes the participation of netizens in the environmental protection event from at least one dimension, including netizen distribution, age, gender, and participation method, to obtain a user profile of the netizens. Based on the target public opinion information, an event development trend diagram is obtained, which includes at least one key node of the event. Conduct a positive and negative stance analysis of media reports and netizens' opinions on the aforementioned environmental incident, and obtain the results of the stance analysis; The environmental incident report is generated based on the described demographic profile, the schematic diagram of the event's development trend, and the results of the position analysis. The step of automatically and intelligently analyzing the online participation in the environmental event from at least one dimension, including online user distribution, age, gender, and participation method, to obtain a user profile, includes: The public behavior in the public opinion information to be analyzed is analyzed and mined to extract users' interest characteristics and focus, and spatial analysis methods are combined to extract the spatial areas that users are interested in. The steps of analyzing and mining public behavior in the public opinion information to be analyzed, extracting users' interest characteristics and focus, and extracting spatial areas of interest to users using spatial analysis methods include: Based on a multi-dimensional context-aware computing model, the basic context information of users is determined, and users are further classified and summarized into a set of basic user types with spatiotemporal characteristics and focus of attention. Automatically label user contextual information and extract user interest feature data; Spatial labeling of user interest areas, combined with analysis of connections with surrounding environmental pollution sources and ecologically sensitive areas, reveals the range of spatial areas that users are interested in. The steps for determining the user's basic contextual information based on the multidimensional context-aware computing model include: Establish a PDA multidimensional emotion model, where P represents pleasure, used to represent the positive and negative characteristics of an individual's emotional state, A represents activation, used to represent an individual's neurophysiological activation level, and D represents dominance, used to represent an individual's influence on or being influenced by the situation and others. The sentiment computing database is divided into a text database and an icon database according to its form. The text database is divided into five sentiment categories, namely strong positive, weak positive, neutral, weak negative, and strong negative. The icon database includes a variety of commonly used icons, each of which is assigned a different level of emotion. The sentiment text in the text database and the icons in the icon database are assigned different scores of P-value and A-value. The PDA multi-dimensional sentiment model is used to analyze the public opinion information to be analyzed, and the final P value and A value are obtained. The D value, as the coefficient of the function corresponding to the P value and A value, needs to be associated with spatial labeling and set between 0.1 and 2. The P value is labeled according to user behavior or labeled by the user himself. The user's basic contextual information is determined based on the final A, P, and D values.

10. An analysis module of an intelligent environmental protection platform ecological environment public opinion monitoring system, characterized in that, It includes a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method as described in any one of claims 1 to 8.

11. The analysis module of the intelligent environmental protection platform ecological environment public opinion monitoring system according to claim 10, characterized in that, The intelligent environmental protection platform's ecological environment public opinion monitoring system block includes a storage medium storing a computer program. When the computer program is executed by a processor, the processor performs the steps of the method as described in any one of claims 1 to 8.

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