Automatic management and control method and device for treating false information
By implementing automatic control methods on social media platforms, using false information knowledge base and event database for information matching and analysis, generating early warning information, solving the problem of difficult-to-control dissemination of false information, real-time monitoring and effective control of false information events are achieved.
Patent Information
- Application Number
- CN202411630191.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-15
- Publication Date
- 2025-03-11
AI Technical Summary
The development of Internet technology has led to the spread of false information faster, and it is difficult for existing technologies to effectively regulate and control the spread of false information.
It provides an automatic control method and device for controlling false information. By obtaining information hotspots on social media network platforms, using preset false information knowledge bases and event databases to match information, determine the nature of the event, generate early warning information, and push it to various social media platforms.
Real-time monitoring and analysis of false information events on social media network platforms is realized, timely and effectively control the spread of false information events, and prevent the proliferation of false information.
Smart Images
Figure CN119599688A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of false information control, and in particular to an automatic control method and device for managing false information. Background Art
[0002] The rapid development of Internet technology has reduced the cost of producing false information and caused it to spread more quickly. Therefore, there is an urgent need for a technical means to automatically control false information. Summary of the invention
[0003] The purpose of this application is to provide an automatic management and control method and device for managing false information, which can timely and effectively supervise and control the spread of false information on social media network platforms.
[0004] To achieve the above objectives, this application provides the following solutions:
[0005] In the first aspect, the present application provides an automatic control method for managing false information, including:
[0006] Obtain information hot events on social media network platforms;
[0007] When the spread heat of the information hotspot event reaches a preset threshold, information matching is performed on the information hotspot event according to a preset false information knowledge base and a preset false information event library to obtain the nature and spread trend of the information hotspot event;
[0008] When the nature of the information hotspot event is determined to be false information, generating early warning information of the information hotspot event according to the nature and dissemination trend of the information hotspot event;
[0009] The warning information is pushed to each of the social media network platforms.
[0010] In the second aspect, the present application provides an automatic control device for managing false information, including:
[0011] A false information knowledge base, which is used to store historical false text information, historical false image information, historical false video information, historical false audio information, and historical multimodal mixed false information;
[0012] The false information event database is used to store historical false event information; the historical false event information includes the propagation time, propagation path, propagation population, propagation scope and propagation curve of the false event;
[0013] A hot event acquisition module is used to obtain information hot events on social media network platforms;
[0014] A trigger and calculation module is used to match the information hotspot event with the preset false information knowledge base and the preset false information event library when the spread heat of the information hotspot event reaches a preset threshold, so as to obtain the nature and spread trend of the information hotspot event;
[0015] The feedback module is used to generate early warning information of the information hotspot event according to the nature and dissemination trend of the information hotspot event when the nature of the information hotspot event is determined to be false information, and push the early warning information to each of the social media network platforms.
[0016] In a third aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned automatic management and control method for managing false information.
[0017] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned automatic management and control method for managing false information.
[0018] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above-mentioned automatic management and control method for managing false information.
[0019] According to the specific embodiments provided in this application, this application discloses the following technical effects:
[0020] The present application provides an automatic control method and device for managing false information, the method comprising obtaining information hot events on a social media network platform; when the spread heat of the information hot event reaches a preset threshold, information matching is performed on the information hot event according to a preset false information knowledge base and a preset false information event library, and the nature and spread trend of the information hot event is obtained; when the nature of the information hot event is determined to be false information, early warning information of the information hot event is generated according to the nature and spread trend of the information hot event; and the early warning information is pushed to each of the social media network platforms. The present invention can monitor the information hot events on the social media network platform in real time. Once the spread heat of the event reaches a certain threshold, the information hot event will be analyzed to determine the nature of the event, and early warning information will be sent to each social media network platform, which can not only monitor the false hot events appearing on the social media network platform in real time, but also can timely and effectively control the spread of false information events. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0022] Figure 1 This is an application environment diagram of an automatic control method for managing false information in one embodiment of the present application;
[0023] Figure 2 A flowchart of an automatic control method for managing false information provided in one embodiment of the present application;
[0024] Figure 3 A schematic diagram of functional modules of an automatic control method and device for managing false information provided in one embodiment of the present application;
[0025] Figure 4 A schematic diagram of the relationship between the automatic control method and device for managing false information provided in one embodiment of the present application and various social media network platforms;
[0026] Figure 5 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION
[0027] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0028] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.
[0029] The automatic control method for managing false information provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal communicates with the server through the network. The data storage system can store data that the server needs to process. The data storage system can be set up separately, integrated on the server, or placed on the cloud or other servers. The terminal can send information hot events on the social media network platform to the server, and the server obtains the information hot events on the social media network platform; when the spread of the information hot event reaches a preset threshold, the information hot event is matched according to the preset false information knowledge base and the preset false information event library, and the nature and spread of the information hot event are obtained; when the nature of the information hot event is determined to be false information, the information hot event is generated according to the nature and spread of the information hot event. Early warning information; step 104, the early warning information is pushed to each of the social media network platforms. The server can feedback the obtained early warning information of the information hot event to the terminal.
[0030] The terminal may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The server may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.
[0031] In an exemplary embodiment, Figure 2 As shown, an automatic control method for managing false information is provided, which is executed by a computer device. In an embodiment of the present application, the method is applied to Figure 1 The server in the example is used to illustrate, including the following steps 101 to 104. Among them:
[0032] Step 101, obtaining hot information events on a social media network platform.
[0033] Step 102, when the spread heat of the information hotspot event reaches a preset threshold, information matching is performed on the information hotspot event according to a preset false information knowledge base and a preset false information event library to obtain the nature and spread trend of the information hotspot event.
[0034] Among them, the spread heat refers to the spread range of a hot event within a certain unit of time (the spread range refers to the number of people who spread the event, and in the network it refers to the number of network nodes that spread the event).
[0035] The preset false information knowledge base stores historical false text information, historical false image information, historical false video information, historical false audio information, and historical multimodal mixed false information. The preset false information event library stores historical false event information that has occurred frequently in the past; historical false event information includes the propagation time, propagation path, propagation population, propagation range, and propagation curve of the false event. The two core databases are used to make comparative analysis of current hot events.
[0036] Step 103: When the nature of the information hotspot event is determined to be false information, early warning information of the information hotspot event is generated according to the nature and propagation trend of the information hotspot event.
[0037] Step 104: Push the warning information to each of the social media network platforms.
[0038] By implementing the above steps 101 to 104, the present invention can monitor information hot events on social media network platforms in real time. Once the spread of an event reaches a certain threshold, it will analyze the information hot event, determine the nature of the event, and send early warning information to each social media network platform. It can not only monitor the false hot events appearing on the social media network platform in real time, but also control the spread of false information events in a timely and effective manner.
[0039] In another exemplary embodiment of the present application, for step 102, information matching is performed on the information hotspot event according to a preset false information knowledge base and a preset false information event base to obtain the nature and propagation trend of the information hotspot event, specifically including:
[0040] Based on the false information stored in a preset false information knowledge base and the false information events stored in a preset false information event library, modal alignment technology and pattern recognition technology are used to analyze the sensitive words, propagation paths, propagation laws, propagation scope, propagation time, propagation population and propagation curves of the information hotspot events to obtain the nature and propagation trend of the information hotspot events.
[0041] Among them, modal alignment technology and pattern recognition technology use existing technologies. Modal alignment technology refers to establishing associations between different modalities, with the goal of effectively representing and integrating data of different modalities such as text, images, audio and video in the same feature space. Pattern recognition technology refers to using computational methods to divide samples into certain categories based on their characteristics. Here, it is used to compare hot events with false event information stored in the false information event library to determine whether the current hot event is a false event.
[0042] Sensitive words, propagation curves, propagation rules, propagation paths, propagation ranges, and propagation characteristics. These contents are expressed differently when false information is propagated and when normal information is propagated. For example, sensitive words: false information events have a distinct writing style. Propagation curves: the propagation curves of false events have a clear exponential upward trend. Propagation ranges: the propagation ranges of false events have more obvious cluster propagation characteristics. These are used to reflect the propagation of hot events and to determine whether they are false events.
[0043] In another exemplary embodiment of the present application, for step 104, pushing the warning information to each of the social media network platforms specifically includes:
[0044] The warning information is pushed to each of the social media network platforms using network broadcast distribution technology, so that each social media network platform can control the spread of the information hotspot event.
[0045] The present application also provides an application scenario, which applies the above-mentioned automatic control method for managing false information. Specifically: The automatic control method for managing false information provided in this embodiment can be applied in the false information control scenario in the social media network platform. The scenario includes the hot event information collection link, the hot event analysis link and the analysis result display link. The automatic control method for managing false information provided in this embodiment belongs to the hot event analysis link.
[0046] Based on the same inventive concept, the embodiment of the present application also provides an automatic control device for managing false information for implementing the automatic control method for managing false information involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the automatic control device for managing false information provided below can refer to the limitations of the automatic control method for managing false information above, and will not be repeated here.
[0047] In an exemplary embodiment, Figure 3 As shown, an automatic control device for managing false information is provided, including:
[0048] The false information knowledge base M1 is used to store historical false text information, historical false picture information, historical false video information, historical false audio information and historical multimodal mixed false information.
[0049] The false information event database M2 is used to store historical false event information; the historical false event information includes the propagation time, propagation path, propagation population, propagation scope and propagation curve of the false event.
[0050] The false information knowledge base and false information event base provide big data computing support for the trigger and computing module M4.
[0051] The hot event acquisition module M3 is used to obtain information hot events on the social media network platform.
[0052] The trigger and calculation module M4 is used to match the information hotspot event with the preset false information knowledge base and the preset false information event library when the spread heat of the information hotspot event reaches a preset threshold, so as to obtain the nature and spread trend of the information hotspot event.
[0053] The trigger and calculation module M4 uses information control trigger technology to trigger the automatic control of collaborative governance of false information when the popularity of information hot events on various social media reaches a certain threshold; then, relying on the core database (false information knowledge base and false information event database), it performs calculations such as keyword matching and propagation curve comparison on information hot events, analyzes and calculates the propagation path, rules, scope, and characteristics of information hot events, and determines the nature and propagation trend of the hot events.
[0054] The feedback module M5 is used to generate warning information of the information hotspot event according to the nature and dissemination trend of the information hotspot event when the nature of the information hotspot event is determined to be false information, and push the warning information to each of the social media network platforms.
[0055] The feedback module M5 converts the information calculation results into warning information, and uses network broadcast distribution technology to push the warning information to the social media network platforms of various media companies. The social media network platforms guide and control the dissemination of the hot event information.
[0056] In response to the problems of low coordination efficiency and difficulty in sharing data between administrative regulatory agencies and media companies, as well as between media companies, in the comprehensive social governance of false information on the Internet, the national competent authorities have been exploring data sharing mechanisms with Internet companies, coordinating local competent authorities and media companies to conduct collaborative governance. Designed from the perspective of collaborative governance between national administrative regulatory agencies and various corporate social media platforms, the automatic control device for managing false information can be used as an automatic control system for collaborative governance of false information between government and enterprises, in order to achieve the purpose of collaborative governance between regulatory agencies and media platforms and effectively curb the spread of false information. Therefore, as an example, the automatic control device for managing false information can be used as an automatic control system for collaborative governance of false information between government and enterprises. Administrative regulatory agencies manage the system and connect various social media network platforms to the system, such as Figure 4As shown in the figure, real-time monitoring of hot information events on social media network platforms, analysis and calculation of false information, generation of early warning information based on the calculation results, and push to various social media network platforms have effectively controlled the spread of false information, achieved supervision by administrative agencies and control by media platforms, and coordinated control of false information on the Internet by government and enterprises, achieving the effect of administrative regulatory agencies and various social media network platforms jointly governing social media network space, and various social media networks sharing false information knowledge base and false information event base, two core databases led by administrative regulatory agencies. Finally, the data sharing, joint prevention and joint governance of the network space by the whole media industry and the local administrative regulatory agencies are completed, and the proliferation of false information is jointly curbed. The collaborative governance between administrative regulatory agencies and various media companies, with the national administrative regulatory agency as the information exchange center, achieves administrative agencies supervising media companies, various media companies controlling the spread of false information, and government and enterprises jointly governing false information, and joint prevention and control effectively curbs the spread of false information.
[0057] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store false information data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an automatic control method for managing false information is implemented.
[0058] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.
[0059] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.
[0060] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.
[0061] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.
[0062] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).
[0063] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.
[0064] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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.
[0065] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.
Claims
1. An automatic control method for managing false information, characterized in that: The automatic control method for managing false information includes: Obtain information hot events on social media network platforms; When the spread heat of the information hotspot event reaches a preset threshold, information matching is performed on the information hotspot event according to a preset false information knowledge base and a preset false information event library to obtain the nature and spread trend of the information hotspot event; When the nature of the information hotspot event is determined to be false information, generating early warning information of the information hotspot event according to the nature and dissemination trend of the information hotspot event; The warning information is pushed to each of the social media network platforms.
2. The automatic control method for managing false information according to claim 1 is characterized in that: The preset false information knowledge base stores historical false text information, historical false picture information, historical false video information, historical false audio information and historical multimodal mixed false information; The preset false information event library stores historical false event information; the historical false event information includes the propagation time, propagation path, propagation population, propagation scope and propagation curve of the false event.
3. The automatic control method for managing false information according to claim 1 is characterized in that: According to the preset false information knowledge base and the preset false information event base, information matching is performed on the information hotspot event to obtain the nature and propagation trend of the information hotspot event, specifically including: According to the false information stored in the preset false information knowledge base and the false information events stored in the preset false information event library, the propagation path, propagation law, propagation scope, propagation time, propagation population and propagation curve of the information hotspot events are analyzed by using modal alignment technology and pattern recognition technology to obtain the nature and propagation trend of the information hotspot events.
4. The automatic control method for managing false information according to claim 1 is characterized in that: Pushing the warning information to each of the social media network platforms specifically includes: The warning information is pushed to each of the social media network platforms using network broadcast distribution technology, so that each social media network platform can control the spread of the information hotspot event.
5. An automatic control device for managing false information, characterized in that: The automatic control device for managing false information includes: A false information knowledge base, which is used to store historical false text information, historical false image information, historical false video information, historical false audio information, and historical multimodal mixed false information; The false information event database is used to store historical false event information; the historical false event information includes the propagation time, propagation path, propagation population, propagation scope and propagation curve of the false event; A hot event acquisition module is used to obtain information hot events on social media network platforms; A trigger and calculation module is used to match the information hotspot event with the preset false information knowledge base and the preset false information event library when the spread heat of the information hotspot event reaches a preset threshold, so as to obtain the nature and spread trend of the information hotspot event; The feedback module is used to generate early warning information of the information hotspot event according to the nature and dissemination trend of the information hotspot event when the nature of the information hotspot event is determined to be false information, and push the early warning information to each of the social media network platforms.
6. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the automatic control method for managing false information as described in any one of claims 1 to 4.
7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the automatic control method for managing false information as described in any one of claims 1 to 4.
8. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, it implements the automatic control method for managing false information as described in any one of claims 1 to 4.