CN116561324B - Network information intelligent analysis regulation and control system and method based on artificial intelligence - Google Patents
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Abstract
The invention discloses an intelligent network information analysis and regulation system and method based on artificial intelligence, and belongs to the technical field of data processing. The system comprises a data acquisition module, a data processing module, a function control module and a data storage module; the data acquisition module is used for acquiring manuscript information, propagation information and account information; the data processing module judges the account type through the account information, and comprehensively calculates the credibility of the manuscript through the manuscript information and the propagation information, so as to judge the manuscript type; the function control module sets a propagation state according to the manuscript type and the account type, and achieves behavior control of the account propagation manuscript through the propagation state; the data storage module is used for carrying out backup storage on all the information. The invention analyzes the document propagation track and account behavior to judge whether the document is illegal or not and whether the account is normal or not, thereby realizing the control and management of bad information propagation.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an intelligent network information analysis and regulation system and method based on artificial intelligence.
Background
With the rapid development of the information society, the speed and the range of information transmission are greatly improved, more convenience is brought to people, and the information transmission system also becomes an important channel for public opinion transmission. A small thing in daily life can quickly spread fermentation on the internet, and finally seriously deviate from the fact, so that the small thing becomes a public opinion event with great influence, and serious threat is brought to the stability and public safety of society. Therefore, the method has important practical significance for research and prevention of public opinion.
The monitoring and control of public opinion at present is mainly focused on information carriers, such as: text, short video or audio information. And extracting key information by adopting modes such as big data, cloud computing or artificial intelligence, and identifying whether the information is a false message or an unproven message. In the aspect of information propagators, an account security mode is mainly adopted for management, and strong association management with propagated information cannot be achieved. As an important unit in the information spreading process, the information propagator can perform strong association management on the information propagator and the information, and can realize the discovery and control of public opinion in the initial stage of spreading, so that the problem is forced to be solved.
Disclosure of Invention
The invention aims to provide an artificial intelligence based network information intelligent analysis and regulation system and method, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the system comprises a data acquisition module, a data processing module, a function control module and a data storage module.
The data acquisition module is used for acquiring manuscript information, propagation information and account information; the data processing module judges the account type through the account information, and comprehensively calculates the credibility of the manuscript through the manuscript information and the propagation information, so as to judge the manuscript type; the function control module sets a propagation state according to the manuscript type and the account type, and achieves behavior control of the account propagation manuscript through the propagation state; the data storage module is used for carrying out backup storage on all the information.
The data acquisition module comprises an account information acquisition unit, a manuscript information acquisition unit and a propagation information acquisition unit.
The account information acquisition unit is used for acquiring browsing time information and historical record information of all accounts in the monitoring range. The manuscript information acquisition unit is used for acquiring the release source information and the content theme information of all manuscripts in the monitoring range. The propagation information acquisition unit is used for acquiring propagation group information and propagation probability information corresponding to all the manuscripts in the monitoring range.
All accounts refer to all active accounts within the monitoring range that are browsing documents, and all documents refer to documents being browsed and documents that are historically propagated by active accounts.
The browsing time information of the account refers to the time spent by a user for browsing the manuscript for the first time until the manuscript is propagated; the history information refers to all the propagated manuscript records in the history of the account. The release source information of the manuscript refers to the type of a manuscript publisher, wherein the type of the publisher comprises organization unit media, public institution media, enterprise media and self media; the content subject information refers to the content of the manuscript itself; the propagation group information refers to account types for propagating the manuscript, wherein the account types comprise normal accounts and abnormal accounts; the propagation probability information refers to the read-forward rate of the document.
The data processing module comprises a manuscript type judging unit and an account type judging unit.
The manuscript type judging unit is used for judging the types of all manuscripts in the monitoring range; the manuscript type includes regular information, unproven information, and violation information.
Firstly, analyzing according to manuscript source information, judging the type of a manuscript publisher, wherein the type of the publisher is a institution unit medium or a public institution medium, and setting the corresponding manuscript type as conventional information; secondly, analyzing the content subject information of the manuscript by a natural language processing technology, judging whether extremely emotional vocabulary, sensitive vocabulary or violation of basic common knowledge exist, and setting the corresponding manuscript type as violation information if the extremely emotional vocabulary, the sensitive vocabulary or the violation of basic common knowledge exist; and finally, collecting propagation group information and propagation probability information of the remaining undefined type manuscript, wherein the propagation group information refers to an account type for propagating the manuscript, the propagation probability information refers to the read forwarding rate of the manuscript, and substituting the account type and the read forwarding rate of the corresponding type into a formula to calculate the credibility of the manuscript. Different manuscript types are divided according to the credibility of the manuscript.
Judging whether the credibility of the manuscript is in a credibility threshold value interval or not: setting the manuscript type as an unproven message when the manuscript is in the interval; setting the manuscript type as a conventional message when the manuscript type is larger than the interval; and if the document type is smaller than the interval, setting the document type as an offending message.
The account type judging unit is used for judging the types of all accounts in the monitoring range; the corresponding account types are divided through the browsing time information and the history record information of the account, and the account types comprise normal accounts and abnormal accounts.
Firstly judging whether the account browsing time is greater than or equal to the shortest reading time, if the result is not the result, the account browsing time is unreasonable, the account belongs to the behavior of no-reading propagation, and the account type is set as an abnormal account; if the result is yes, the user browsing time is reasonable, and the method belongs to the post-reading propagation behavior. Continuing to analyze the account history record, judging whether the proportion of the violation information in the account history record information is greater than or equal to the maximum proportion of the violation information, if so, indicating that the account history behavior is reasonable, belonging to normal propagation behavior, and setting the account type as a normal account; if the result is yes, the account history behavior is unreasonable, the account belongs to abnormal propagation behavior, and the account type is set as an abnormal account.
The normal account means that the user using the account acts normally, and the browsing time information and the history information are in a normal range. The abnormal account refers to abnormal behavior of a user using the account, too short a document browsing time or too high a history propagation document type violation information ratio, and all the behaviors can lead to the account type to be divided into the abnormal accounts.
In general, if the browsing time of the user is greater than or equal to the shortest reading time and less than the shortest reading time, it is indicated that the browsing of the user is abnormal and account risk exists. The history information comprises the history propagation manuscript type and the times of the account, and whether the user of the account is a real user or not and whether the user normally uses the account are judged by analyzing whether the history propagation manuscript type is illegal information and calculating the percentage of the illegal information to the total number of the history records.
The function control module comprises a propagation state setting unit and a propagation state control unit.
The propagation state setting unit is used for setting states of the account when propagating the manuscript. And setting the propagation state according to the manuscript type and the account type through comprehensive judgment. Propagation states include unlimited propagation, limited propagation, and prohibited propagation.
When the document type is conventional information, the propagation state is unlimited propagation. Judging the propagation account type when the manuscript type is the unlicensed information: the account type is a normal account, and the propagation state is a propagation limiting A; the account type is an anomalous account and the propagation state is a constraint propagation B. When the manuscript type is illegal information, the propagation state is forbidden to propagate.
The propagation state control unit is used for controlling the behavior of the account propagation manuscript. According to the propagation state set by the propagation state setting unit, the behavior of each account propagation manuscript is controlled, and the control comprises unlimited propagation, forbidden propagation, limited propagation A and limited propagation B.
Unlimited propagation refers to propagation of any type of account number without limitation to the propagation of the document. The prohibition of the propagation refers to limiting the propagation of the manuscript, and account numbers in any state can not be propagated. Limiting propagation a refers to prompting prior to propagation, prompting that the manuscript information is unproven information. Limiting propagation B refers to prompting prior to propagation, prompting that the manuscript information is unproven information and reducing the number of people that can browse after propagation.
The data storage module is used for storing the manuscript type, the account type and the propagation state information into a database for tracing operation.
An intelligent network information analysis and regulation method based on artificial intelligence comprises the following steps:
s1, collecting information of all accounts and manuscripts in a monitoring range in real time;
s2, judging the manuscript type and the account type when the account propagates the manuscript;
s3, setting a propagation state according to the manuscript type and the account type;
s4, controlling the behavior of the account propagation manuscript through the propagation state.
In S1, accounts refer to all active accounts within the monitoring range that are browsing documents, and documents refer to documents being browsed and documents that are historically propagated by active accounts. The collected information comprises release source information and content subject information of the manuscript, propagation group information and propagation probability information corresponding to the manuscript, and browsing time information and history information of the account.
In S2, the document type and account type judgment steps are as follows:
s201, analyzing release source information of all the manuscripts, wherein no matter whether the manuscripts are forwarded or original, only one corresponding manuscripts release, finding out the manuscripts release, judging the types of the manuscripts release, wherein the release types are organization unit media or public institution media, and setting the corresponding manuscripts as conventional information. The publisher type is enterprise media or self media, and the next step is entered.
S202, respectively constructing an extreme emotion vocabulary ontology library, a sensitive vocabulary ontology library and a basic common sense ontology library, and combining the extreme emotion vocabulary ontology library, the sensitive vocabulary ontology library and the basic common sense ontology library into a knowledge base. Preprocessing the content theme information of the rest non-set type manuscript by using a natural language processing technology, extracting keywords by using an LDA theme model, and obtaining 2 probability distributions of a document-theme and a theme-word.
And S203, matching the extracted keywords with a knowledge base, and judging whether extreme emotional vocabulary, sensitive vocabulary or violation of the basic common sense exists. As a result, the corresponding document type is set as the offending information, and as a result, no, the next step is entered.
S204, collecting propagation group information and propagation probability information of the rest non-set type manuscripts, wherein the propagation group information refers to account types for propagating the manuscripts, the propagation probability information refers to the read forwarding rate of the manuscripts, and substituting the total account type number and the read forwarding rate of different types of each manuscript into a formula to calculate the credibility of the manuscript; the formula is as follows:
KXD=a×(e positive direction ÷e Total (S) )×f Positive direction -b×（e Different species ÷e Total (S) ）×f Different species
Wherein KXD is the credibility of the manuscript, a is the influence coefficient of the credibility of the normal account, e Positive direction E, corresponding to the number of normal accounts in the propagation group information for the manuscript Total (S) For the corresponding propagation of all account numbers in group information, f Positive direction For the read forwarding rate of normal accounts in the corresponding propagation group information of the manuscript, b is an abnormal account credibility influence coefficient, e Different species For the number of abnormal accounts in the corresponding propagation group information of the manuscript, f Different species And correspondingly transmitting the read forwarding rate of the abnormal account in the group information for the manuscript.
S205, judging whether the credibility of the manuscript is in a credibility threshold interval, and setting the manuscript type as an unproven message if the credibility of the manuscript is in the credibility threshold interval; setting the manuscript type as a conventional message when the credibility threshold interval maximum value is larger than the credibility threshold interval maximum value; setting the manuscript type as the violation message if the credibility threshold interval minimum value is smaller than the credibility threshold interval minimum value;
s206, judging whether the account browsing time is greater than or equal to the shortest reading time, if the result is not, indicating that the user browsing time is unreasonable, belonging to the non-reading propagation behavior, judging that the result is abnormal, and setting the account type as an abnormal account. The result is that the browsing time of the user is reasonable, the browsing time belongs to the after-reading propagation behavior, the judgment result is normal, and the next step is entered.
The shortest reading time is set according to the number of the manuscript content words, and the shortest reading time is obtained by dividing the number of the manuscript content words by the fastest reading speed. The browsing time information refers to the time spent by the user for browsing the manuscript for the first time until the manuscript is propagated, and the browsing time is smaller than the shortest reading time, which indicates that the user starts forwarding without reading the content of the article, and the operation behavior is abnormal, so that junk information can be maliciously propagated or the junk information does not belong to a real user, and the account needs to be limited.
S207, analyzing the account history record, judging whether the ratio of the violation information in the account history record information is larger than or equal to the maximum ratio of the violation information, if not, indicating that the account history behavior is reasonable, belonging to normal propagation behavior, judging that the result is normal, and setting the account type as a normal account. The result is that the account history behavior is unreasonable, the account history behavior belongs to abnormal propagation behavior, the judgment result is abnormal, and the account type is set as an abnormal account.
The maximum duty ratio of the violation information is a fixed value, and is set according to the actual situation, wherein the maximum value is not more than 100%, and the larger the value is, the more loose the examination is. The history record comprises all manuscript transmission records of the account, the manuscript type of each transmission record is analyzed, the number of recorded manuscripts with the manuscript type being illegal information is divided by the total number of recorded manuscripts to obtain the ratio of the illegal information, the ratio is larger than or equal to the maximum ratio of the illegal information to indicate that the operation behavior of the account is abnormal, and the account is possibly maliciously transmitted with illegal information or not belonging to a real user and needs to be limited.
In S3, the setting step of the propagation state is as follows:
s301, when the manuscript type is conventional information, setting the propagation state as unlimited propagation.
S302, when the manuscript type is illegal information, the propagation state is set to be forbidden to propagate.
S303-1, when the manuscript type is the non-verified information, entering into S303-2.
S303-2, continuing to judge the type of the propagation account, wherein the type of the account is a normal account, and the propagation state is set as a propagation limiting A; the account type is an anomalous account and the propagation state is set to limit propagation B.
In S4, the propagation states include unlimited propagation, prohibited propagation, limited propagation a, and limited propagation B. The specific control mode is as follows:
unlimited propagation means that any state account number can be propagated without limiting the propagation of the document. The prohibition of the propagation refers to limiting the propagation of the manuscript, and account numbers in any state can not be propagated. The propagation restriction A refers to popup window prompt before propagation, the text draft information is not verified, and the propagation can be performed after a user clicks a confirmation button. Limiting propagation B refers to popup window prompting before propagation, prompting that the manuscript information is unproven information, and the user can propagate after clicking the confirm button, but the number of people who can see after propagation is reduced.
Compared with the prior art, the invention has the following beneficial effects:
the invention comprehensively judges the browsing information and the history information of the user, judges whether the browsing information and the history information are abnormal according to the behavior of the user, and realizes different restrictions of different types of accounts when the manuscript is transmitted.
The invention firstly sets the manuscript type by screening manuscript source information and judging content subject information, if the manuscript type is not set successfully, then calculates the credibility of the manuscript according to manuscript propagation group information and propagation probability information, thereby setting the manuscript type, reducing the consumption of system resources, simultaneously updating the manuscript type in real time and managing and controlling self-adaptive public opinion.
According to the method, the propagation state is set in a mode that the account and the manuscript are strongly associated, the account and the manuscript are mutually influenced, the account type is influenced by repeated transmission of illegal information by a single account, the manuscript type is influenced by repeated transmission of abnormal account by a single manuscript, and double control of public opinion is achieved.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of a system and method for intelligent analysis and control of network information based on artificial intelligence;
FIG. 2 is a schematic flow chart of an intelligent analysis and control system and method for network information based on artificial intelligence.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides the following technical solutions: the system comprises a data acquisition module, a data processing module, a function control module and a data storage module.
The data acquisition module is used for acquiring manuscript information, propagation information and account information; the data processing module judges the account type through the account information, and comprehensively calculates the credibility of the manuscript through the manuscript information and the propagation information, so as to judge the manuscript type; the function control module sets a propagation state according to the manuscript type and the account type, and achieves behavior control of the account propagation manuscript through the propagation state; the data storage module is used for carrying out backup storage on all the information.
The data acquisition module comprises an account information acquisition unit, a manuscript information acquisition unit and a propagation information acquisition unit.
The account information acquisition unit is used for acquiring browsing time information and historical record information of all accounts in the monitoring range. The manuscript information acquisition unit is used for acquiring the release source information and the content theme information of all manuscripts in the monitoring range. The propagation information acquisition unit is used for acquiring propagation group information and propagation probability information corresponding to all the manuscripts in the monitoring range.
All accounts refer to all active accounts within the monitoring range that are browsing documents, and all documents refer to documents being browsed and documents that are historically propagated by active accounts.
The browsing time information of the account refers to the time spent by a user for browsing the manuscript for the first time until the manuscript is propagated; the history information refers to all the propagated manuscript records in the history of the account. The release source information of the manuscript refers to the type of a manuscript publisher, wherein the type of the publisher comprises organization unit media, public institution media, enterprise media and self media; the content subject information refers to the content of the manuscript itself; the propagation group information refers to account types for propagating the manuscript, wherein the account types comprise normal accounts and abnormal accounts; the propagation probability information refers to the read-forward rate of the document.
The data processing module comprises a manuscript type judging unit and an account type judging unit.
The manuscript type judging unit is used for judging the types of all manuscripts in the monitoring range; the manuscript type includes regular information, unproven information, and violation information.
Firstly, analyzing according to manuscript source information, judging the type of a manuscript publisher, wherein the type of the publisher is a institution unit medium or a public institution medium, and setting the corresponding manuscript type as conventional information; secondly, analyzing the content subject information of the manuscript by a natural language processing technology, judging whether extremely emotional vocabulary, sensitive vocabulary or violation of basic common knowledge exist, and setting the corresponding manuscript type as violation information if the extremely emotional vocabulary, the sensitive vocabulary or the violation of basic common knowledge exist; and finally, collecting propagation group information and propagation probability information of the remaining undefined type manuscript, wherein the propagation group information refers to an account type for propagating the manuscript, the propagation probability information refers to the read forwarding rate of the manuscript, and substituting the account type and the read forwarding rate of the corresponding type into a formula to calculate the credibility of the manuscript. Different manuscript types are divided according to the credibility of the manuscript.
Judging whether the credibility of the manuscript is in a credibility threshold value interval or not: setting the manuscript type as an unproven message when the manuscript is in the interval; setting the manuscript type as a conventional message when the manuscript type is larger than the interval; and if the document type is smaller than the interval, setting the document type as an offending message.
The account type judging unit is used for judging the types of all accounts in the monitoring range; the corresponding account types are divided through the browsing time information and the history record information of the account, and the account types comprise normal accounts and abnormal accounts.
Firstly judging whether the account browsing time is greater than or equal to the shortest reading time, if the result is not the result, the account browsing time is unreasonable, the account belongs to the behavior of no-reading propagation, and the account type is set as an abnormal account; if the result is yes, the user browsing time is reasonable, and the method belongs to the post-reading propagation behavior. Continuing to analyze the account history record, judging whether the proportion of the violation information in the account history record information is greater than or equal to the maximum proportion of the violation information, if so, indicating that the account history behavior is reasonable, belonging to normal propagation behavior, and setting the account type as a normal account; if the result is yes, the account history behavior is unreasonable, the account belongs to abnormal propagation behavior, and the account type is set as an abnormal account.
The normal account means that the user using the account acts normally, and the browsing time information and the history information are in a normal range. The abnormal account refers to abnormal behavior of a user using the account, too short a document browsing time or too high a history propagation document type violation information ratio, and all the behaviors can lead to the account type to be divided into the abnormal accounts.
In general, if the browsing time of the user is greater than or equal to the shortest reading time and less than the shortest reading time, it is indicated that the browsing of the user is abnormal and account risk exists. The history information comprises the history propagation manuscript type and the times of the account, and whether the user of the account is a real user or not and whether the user normally uses the account are judged by analyzing whether the history propagation manuscript type is illegal information and calculating the percentage of the illegal information to the total number of the history records.
The function control module includes a propagation state setting unit and a propagation state control unit.
The propagation state setting unit is used for setting states when the account propagates the manuscript. And setting the propagation state according to the manuscript type and the account type through comprehensive judgment. Propagation states include unlimited propagation, limited propagation, and prohibited propagation.
When the document type is conventional information, the propagation state is unlimited propagation. Judging the propagation account type when the manuscript type is the unlicensed information: the account type is a normal account, and the propagation state is a propagation limiting A; the account type is an anomalous account and the propagation state is a constraint propagation B. When the manuscript type is illegal information, the propagation state is forbidden to propagate.
The propagation state control unit is used for controlling the behavior of the account propagation manuscript. According to the propagation state set by the propagation state setting unit, the behavior of each account propagation manuscript is controlled, and the control comprises unlimited propagation, forbidden propagation, limited propagation A and limited propagation B.
Unlimited propagation refers to propagation of any type of account number without limitation to the propagation of the document. The prohibition of the propagation refers to limiting the propagation of the manuscript, and account numbers in any state can not be propagated. Limiting propagation a refers to prompting prior to propagation, prompting that the manuscript information is unproven information. Limiting propagation B refers to prompting prior to propagation, prompting that the manuscript information is unproven information and reducing the number of people that can browse after propagation.
The data storage module is used for storing the manuscript type, the account type and the propagation state information into a database for tracing operation.
Referring to fig. 2, the present invention provides a technical solution, an intelligent network information analysis and control method based on artificial intelligence, the method includes the following steps:
s1, collecting information of all accounts and manuscripts in a monitoring range in real time;
s2, judging the manuscript type and the account type when the account propagates the manuscript;
s3, setting a propagation state according to the manuscript type and the account type;
s4, controlling the behavior of the account propagation manuscript through the propagation state.
In S1, accounts refer to all active accounts within the monitoring range that are browsing documents, and documents refer to documents being browsed and documents that are historically propagated by active accounts. The collected information comprises release source information and content subject information of the manuscript, propagation group information and propagation probability information corresponding to the manuscript, and browsing time information and history information of the account.
In S2, the document type and account type judgment steps are as follows:
s201, analyzing release source information of all the manuscripts, wherein no matter whether the manuscripts are forwarded or original, only one corresponding manuscripts release, finding out the manuscripts release, judging the types of the manuscripts release, wherein the release types are organization unit media or public institution media, and setting the corresponding manuscripts as conventional information. The publisher type is enterprise media or self media, and the next step is entered.
S202, respectively constructing an extreme emotion vocabulary ontology library, a sensitive vocabulary ontology library and a basic common sense ontology library, and combining the extreme emotion vocabulary ontology library, the sensitive vocabulary ontology library and the basic common sense ontology library into a knowledge base. Preprocessing the content theme information of the rest non-set type manuscript by using a natural language processing technology, extracting keywords by using an LDA theme model, and obtaining 2 probability distributions of a document-theme and a theme-word.
And S203, matching the extracted keywords with a knowledge base, and judging whether extreme emotional vocabulary, sensitive vocabulary or violation of the basic common sense exists. As a result, the corresponding document type is set as the offending information, and as a result, no, the next step is entered.
S204, collecting propagation group information and propagation probability information of the rest non-set type manuscripts, wherein the propagation group information refers to account types for propagating the manuscripts, the propagation probability information refers to the read forwarding rate of the manuscripts, and substituting the total account type number and the read forwarding rate of different types of each manuscript into a formula to calculate the credibility of the manuscript; the formula is as follows:
KXD=a×(e positive direction ÷e Total (S) )×f Positive direction -b×（e Different species ÷e Total (S) ）×f Different species
Wherein KXD is the credibility of the manuscript, a is the influence coefficient of the credibility of the normal account, e Positive direction E, corresponding to the number of normal accounts in the propagation group information for the manuscript Total (S) For the corresponding propagation of all account numbers in group information, f Positive direction For the read forwarding rate of normal accounts in the corresponding propagation group information of the manuscript, b is an abnormal account credibility influence coefficient, e Different species For the number of abnormal accounts in the corresponding propagation group information of the manuscript, f Different species And correspondingly transmitting the read forwarding rate of the abnormal account in the group information for the manuscript.
S205, judging whether the credibility of the manuscript is in a credibility threshold interval, and setting the manuscript type as an unproven message if the credibility of the manuscript is in the credibility threshold interval; setting the manuscript type as a conventional message when the credibility threshold interval maximum value is larger than the credibility threshold interval maximum value; and setting the manuscript type as the violation message if the credibility threshold interval minimum value is smaller than the credibility threshold interval minimum value.
S206, judging whether the account browsing time is greater than or equal to the shortest reading time, if the result is not, indicating that the user browsing time is unreasonable, belonging to the non-reading propagation behavior, judging that the result is abnormal, and setting the account type as an abnormal account. The result is that the browsing time of the user is reasonable, the browsing time belongs to the after-reading propagation behavior, the judgment result is normal, and the next step is entered.
The shortest reading time is set according to the number of the manuscript content words, and the shortest reading time is obtained by dividing the number of the manuscript content words by the fastest reading speed. The browsing time information refers to the time spent by the user for browsing the manuscript for the first time until the manuscript is propagated, and the browsing time is smaller than the shortest reading time, which indicates that the user starts forwarding without reading the content of the article, and the operation behavior is abnormal, so that junk information can be maliciously propagated or the junk information does not belong to a real user, and the account needs to be limited.
S207, analyzing the account history record, judging whether the ratio of the violation information in the account history record information is larger than or equal to the maximum ratio of the violation information, if not, indicating that the account history behavior is reasonable, belonging to normal propagation behavior, judging that the result is normal, and setting the account type as a normal account. The result is that the account history behavior is unreasonable, the account history behavior belongs to abnormal propagation behavior, the judgment result is abnormal, and the account type is set as an abnormal account.
The maximum duty ratio of the violation information is a fixed value, and is set according to the actual situation, wherein the maximum value is not more than 100%, and the larger the value is, the more loose the examination is. The history record comprises all manuscript transmission records of the account, the manuscript type of each transmission record is analyzed, the number of recorded manuscripts with the manuscript type being illegal information is divided by the total number of recorded manuscripts to obtain the ratio of the illegal information, the ratio is larger than or equal to the maximum ratio of the illegal information to indicate that the operation behavior of the account is abnormal, and the account is possibly maliciously transmitted with illegal information or not belonging to a real user and needs to be limited.
In S3, the setting step of the propagation state is as follows:
s301, when the manuscript type is conventional information, setting the propagation state as unlimited propagation.
S302, when the manuscript type is illegal information, the propagation state is set to be forbidden to propagate.
S303-1, when the manuscript type is the non-verified information, entering into S303-2.
S303-2, continuing to judge the type of the propagation account, wherein the type of the account is a normal account, and the propagation state is set as a propagation limiting A; the account type is an anomalous account and the propagation state is set to limit propagation B.
In S4, the propagation states include unlimited propagation, prohibited propagation, limited propagation a, and limited propagation B. The specific control mode is as follows:
unlimited propagation means that any state account number can be propagated without limiting the propagation of the document. The prohibition of the propagation refers to limiting the propagation of the manuscript, and account numbers in any state can not be propagated. The propagation restriction A refers to popup window prompt before propagation, the text draft information is not verified, and the propagation can be performed after a user clicks a confirmation button. Limiting propagation B refers to popup window prompting before propagation, prompting that the manuscript information is unproven information, and the user can propagate after clicking the confirm button, but the number of people who can see after propagation is reduced.
Embodiment one:
assuming that X, Y and Z are 3 documents in total, X document source is organization unit medium, Y document source is enterprise medium, Z document source is self-medium, where:
setting the X manuscript type as conventional information; extracting keywords from the Y and Z manuscripts by adopting a natural language processing technology, matching the extracted keywords with a knowledge base, and judging whether extreme emotional vocabulary, sensitive vocabulary or violation of basic common knowledge exists;
assuming that the Z manuscript has sensitive vocabulary, and the Y manuscript does not have extremely emotional vocabulary or violate basic common sense;
setting the Z manuscript type as violation information; continuously collecting the total account type number of the transmitted Y manuscript and the read forwarding rate of different types, substituting the total account type number and the read forwarding rate into a formula, calculating to obtain the credibility of the Y manuscript, comparing the credibility with a credibility threshold interval, and judging the type of the Y manuscript;
assuming that the number of normal accounts is 120, the number of abnormal accounts is 60, the forwarding rate of the normal accounts after reading is 10%, the forwarding rate of the abnormal accounts after reading is 5%, the reliability influence coefficient of the normal accounts is 1, and the reliability influence coefficient of the abnormal accounts is 1;
y document credibility: kxd=1× (120++180) ×10% -1× (60++180) ×5+=0.05)
Assuming that the credibility threshold interval is [0,0.1], setting the Y manuscript type as the unproven information when the Y manuscript is in the interval;
the method comprises the steps of obtaining that an X manuscript is conventional information, a Y manuscript type is unlicensed information, and a Z manuscript type is illegal information;
assuming that an account A and an account B are ready to spread an X manuscript, an account C and an account D are ready to spread a Y manuscript, an account E and an account F are ready to spread a Z manuscript, wherein the A browsing time is 25 seconds, the B browsing time is 12 seconds, the C browsing time is 2 seconds, the D browsing time is 36 seconds, the E browsing time is 36 seconds, the F browsing time is 12 seconds, and the shortest reading time is 15 seconds;
b, C and the type of the F account are set as abnormal accounts, and the history information of A, D and E is continuously judged;
assuming that the ratio of the violation information in the A account history information is 25%, the ratio of the violation information in the D account history information is 5%, the ratio of the violation information in the E account history information is 15%, and the maximum ratio of the violation information is 20%;
the account type A is set as an abnormal account, and the account types D and E are set as normal accounts;
obtaining A, B, C and F accounts as abnormal accounts and D and E accounts as normal accounts;
when the propagation operation starts, the propagation state is as follows:
a account (abnormal account) propagates X manuscripts (regular information), propagation status: unlimited propagation;
b account (abnormal account) propagates X manuscript (regular information), propagation status: unlimited propagation;
c account (abnormal account) propagates Y manuscript (non-verified information), propagation status: limiting propagation B;
d account (normal account) propagates Y manuscript (non-verified information), propagation status: limiting propagation a;
e account (normal account) propagates Z manuscript (violation information), propagation status: inhibit propagation;
f account (abnormal account) propagates Z manuscript (violation information), propagation status: propagation is prohibited.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. An artificial intelligence based network information intelligent analysis regulation and control system which is characterized in that: the system comprises a data acquisition module, a data processing module, a function control module and a data storage module;
the data acquisition module is used for acquiring manuscript information, propagation information and account information; the data processing module judges the account type through the account information, and comprehensively calculates the credibility of the manuscript through the manuscript information and the propagation information, so as to judge the manuscript type; the function control module sets a propagation state according to the manuscript type and the account type, and achieves behavior control of the account propagation manuscript through the propagation state; the data storage module is used for carrying out backup storage on all information;
the data processing module comprises a manuscript type judging unit and an account type judging unit;
the manuscript type judging unit is used for judging the types of all manuscripts in the monitoring range; the manuscript type includes regular information, unproven information and violation information;
firstly, analyzing according to manuscript source information, judging the type of a manuscript publisher, wherein the type of the publisher is a institution unit medium or a public institution medium, and setting the corresponding manuscript type as conventional information; secondly, analyzing the content subject information of the manuscript by a natural language processing technology, judging whether extremely emotional vocabulary, sensitive vocabulary or violation of basic common knowledge exist, and setting the corresponding manuscript type as violation information if the extremely emotional vocabulary, the sensitive vocabulary or the violation of basic common knowledge exist; finally, collecting propagation group information and propagation probability information of the rest undefined type manuscript, wherein the propagation group information refers to account types for propagating the manuscript, the propagation probability information refers to the read forwarding rate of the manuscript, and the account types and the read forwarding rates of the corresponding types are substituted into a formula to calculate the credibility of the manuscript; dividing different manuscript types according to the credibility of the manuscript;
the account type judging unit is used for judging the types of all accounts in the monitoring range; dividing corresponding account types by browsing time information and history record information of the account, wherein the account types comprise normal accounts and abnormal accounts;
firstly judging whether the account browsing time is greater than or equal to the shortest reading time, if the result is not the result, the account browsing time is unreasonable, the account belongs to the behavior of no-reading propagation, and the account type is set as an abnormal account; if the result is yes, the user browsing time is reasonable, and the method belongs to the post-reading propagation behavior; continuing to analyze the account history record, judging whether the proportion of the violation information in the account history record information is greater than or equal to the maximum proportion of the violation information, if so, indicating that the account history behavior is reasonable, belonging to normal propagation behavior, and setting the account type as a normal account; if the result is yes, the account history behavior is unreasonable, the account belongs to abnormal propagation behavior, and the account type is set as an abnormal account;
the function control module comprises a propagation state setting unit and a propagation state control unit;
the propagation state setting unit is used for setting states of accounts when propagating manuscripts; setting a propagation state according to the manuscript type and the account type through comprehensive judgment; propagation states include unlimited propagation, limited propagation, and prohibited propagation;
when the manuscript type is conventional information, the propagation state is unlimited propagation; judging the propagation account type when the manuscript type is the unlicensed information: the account type is a normal account, and the propagation state is a propagation limiting A; the account type is an abnormal account, and the propagation state is a propagation limiting B; when the manuscript type is illegal information, the propagation state is forbidden to propagate;
the propagation state control unit is used for controlling the behavior of the account propagation manuscript; according to the propagation state set by the propagation state setting unit, the behavior of each account propagation manuscript is controlled, wherein the control comprises unlimited propagation, forbidden propagation, limited propagation A and limited propagation B;
unlimited propagation refers to propagation of any type of account without limiting the propagation of the manuscript; the forbidden propagation is to limit the propagation of the manuscript, and account numbers in any state can not be propagated; limiting the propagation A means prompting before propagation, and prompting that the manuscript information is unproven information; limiting propagation B refers to prompting prior to propagation, prompting that the manuscript information is unproven information and reducing the number of people that can browse after propagation.
2. The intelligent network information analysis and control system based on artificial intelligence according to claim 1, wherein: the data acquisition module comprises an account information acquisition unit, a manuscript information acquisition unit and a propagation information acquisition unit;
the account information acquisition unit is used for acquiring browsing time information and history record information of all accounts within a monitoring range; the manuscript information acquisition unit is used for acquiring release source information and content theme information of all manuscripts in the monitoring range; the propagation information acquisition unit is used for acquiring propagation group information and propagation probability information corresponding to all the manuscripts in the monitoring range.
3. The intelligent network information analysis and control system based on artificial intelligence according to claim 1, wherein: the data storage module is used for storing the manuscript type, the account type and the propagation state information into a database for tracing operation.
4. An intelligent network information analysis and regulation method based on artificial intelligence is characterized in that: the method comprises the following steps:
s1, collecting information of all accounts and manuscripts in a monitoring range in real time;
s2, judging the manuscript type and the account type when the account propagates the manuscript;
s3, setting a propagation state according to the manuscript type and the account type;
s4, controlling the behavior of the account propagation manuscript through the propagation state;
in S2, the document type and account type judgment steps are as follows:
s201, analyzing release source information of all manuscripts, wherein no matter whether the manuscripts are forwarded or original, only one corresponding manuscripts release, finding out the manuscripts release, judging the types of the manuscripts release, wherein the release types are organization unit media or public institution media, and setting the corresponding manuscripts as conventional information; the type of the publisher is enterprise media or self media, and the next step is entered;
s202, respectively constructing an extreme emotion vocabulary ontology library, a sensitive vocabulary ontology library and a basic common sense ontology library, and combining the extreme emotion vocabulary ontology library, the sensitive vocabulary ontology library and the basic common sense ontology library into a knowledge base; preprocessing content topic information of the rest non-set type manuscript by natural language processing technology, extracting keywords by using an LDA topic model to obtain 2 probability distributions of document-topic and topic-word;
s203, matching the extracted keywords with a knowledge base, and judging whether extreme emotional vocabulary, sensitive vocabulary or violation of basic common knowledge exists; the result is that the corresponding manuscript type is set as the illegal information, if the result is no, the next step is entered;
s204, collecting propagation group information and propagation probability information of the rest non-set type manuscripts, wherein the propagation group information refers to account types for propagating the manuscripts, the propagation probability information refers to the read forwarding rate of the manuscripts, and substituting the total account type number and the read forwarding rate of different types of each manuscript into a formula to calculate the credibility of the manuscript; the formula is as follows:
KXD=a×(e positive direction ÷e Total (S) )×f Positive direction -b×（e Different species ÷e Total (S) ）×f Different species
Wherein KXD is the credibility of the manuscript, a is the influence coefficient of the credibility of the normal account, e Positive direction E, corresponding to the number of normal accounts in the propagation group information for the manuscript Total (S) For the corresponding propagation of all account numbers in group information, f Positive direction For the read forwarding rate of normal accounts in the corresponding propagation group information of the manuscript, b is an abnormal account credibility influence coefficient, e Different species For the number of abnormal accounts in the corresponding propagation group information of the manuscript, f Different species The read forwarding rate of the abnormal account in the corresponding propagation group information of the manuscript;
s205, judging whether the credibility of the manuscript is in a credibility threshold interval, and setting the manuscript type as an unproven message if the credibility of the manuscript is in the credibility threshold interval; setting the manuscript type as a conventional message when the credibility threshold interval maximum value is larger than the credibility threshold interval maximum value; setting the manuscript type as the violation message if the credibility threshold interval minimum value is smaller than the credibility threshold interval minimum value;
s206, judging whether the account browsing time is greater than or equal to the shortest reading time, if the result is negative, indicating that the user browsing time is unreasonable, belonging to the non-reading propagation behavior, judging that the result is abnormal, and setting the account type as an abnormal account; the result is that the browsing time of the user is reasonable, the browsing time belongs to the propagation behavior after reading, the judgment result is normal, and the next step is entered;
s207, analyzing the account history record, judging whether the proportion of the violation information in the account history record information is larger than or equal to the maximum proportion of the violation information, if not, indicating that the account history behavior is reasonable, belonging to normal propagation behavior, judging that the result is normal, and setting the account type as a normal account; the result is that the account history behavior is unreasonable, the account history behavior belongs to abnormal propagation behavior, the result is abnormal, and the account type is set as an abnormal account;
in S3, the setting step of the propagation state is as follows:
s301, when the manuscript type is conventional information, setting a propagation state as unlimited propagation;
s302, when the manuscript type is illegal information, the propagation state is set to be forbidden to propagate;
s303-1, when the manuscript type is the non-verified information, entering into a step S303-2;
s303-2, continuing to judge the type of the propagation account, wherein the type of the account is a normal account, and the propagation state is set as a propagation limiting A; the account type is an anomalous account and the propagation state is set to limit propagation B.
5. The intelligent analysis and regulation method for network information based on artificial intelligence according to claim 4, wherein the intelligent analysis and regulation method is characterized in that: in S1, accounts refer to all active accounts in a monitoring range which are browsing manuscripts, and manuscripts refer to the manuscripts being browsed and the manuscripts of the history propagation of the active accounts; the collected information comprises release source information and content subject information of the manuscript, propagation group information and propagation probability information corresponding to the manuscript, and browsing time information and history information of the account.
6. The intelligent analysis and regulation method for network information based on artificial intelligence according to claim 4, wherein in S4, the propagation state includes unlimited propagation, forbidden propagation, limited propagation a and limited propagation B; the specific control mode is as follows:
unlimited propagation refers to propagation of any state account without limiting the propagation of the manuscript; the forbidden propagation is to limit the propagation of the manuscript, and account numbers in any state can not be propagated; limiting the transmission A means popup window prompt before transmission, prompting that the manuscript information is unproven information, and the user can transmit after clicking the confirm button; limiting propagation B refers to popup window prompting before propagation, prompting that the manuscript information is unproven information, and the user can propagate after clicking the confirm button, but the number of people who can see after propagation is reduced.
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