CN116306587A - Internet negative public opinion early warning method - Google Patents
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Abstract
The invention discloses an internet negative public opinion early warning method, which comprises the following steps: collecting public opinion data information and preprocessing the public opinion data information; carrying out emotion polarity recognition on the preprocessed public opinion data information to identify and mark positive public opinion data information, negative public opinion data information and neutral public opinion data information; performing topic extraction on the negative public opinion data information; calculating an explosion index of the extracted topic and the number of public opinion data information associated with the extracted topic; calculating an emotion index of the extracted topic and positive public opinion data information and negative public opinion data information associated with the extracted topic; calculating a propagation index of the extracted topic and negative public opinion data information associated with the extracted topic; calculating the sum of the extracted burst index, emotion index and propagation index of the same topic to obtain a comprehensive negative public opinion index, and early warning the topic and a corresponding public opinion event when the comprehensive negative public opinion index exceeds a fourth preset threshold.
Description
Technical Field
The invention relates to the technical field of information processing, in particular to an Internet negative public opinion early warning method.
Background
The network public opinion is a popular network public opinion on the Internet and is a representation form of the social public opinion, and the public transmitted through the Internet has a strong influence and tendency on some hot spots and focus problems in real life.
At present, due to certain information difference between network information and audiences, various network negative public opinion events are sudden and frequent, so that the normal public opinion work of related departments is subjected to huge impact, and if the public opinion work cannot be timely dredged and responded, the influence of government speaking right is seriously weakened. However, early warning of negative network public opinion is few at present, and early warning cannot be carried out by simply using negative emotion information of several social networks, so that public opinion work of related departments is greatly hindered.
In view of this, it is necessary to provide an internet negative public opinion early warning method to identify negative public opinion events according to the negative public opinion matters, and implement early warning of the negative public opinion events by calculating the explosion index, emotion index and propagation index of the negative public opinion matters, determining the threshold value, and the like.
Disclosure of Invention
The invention aims to solve the technical problem of providing an Internet negative public opinion early warning method so as to realize early warning prompt of various Internet negative public opinion.
In order to solve the technical problems, an internet negative public opinion early warning method is provided, which comprises the following steps:
collecting public opinion data information from a social network platform, and preprocessing the collected public opinion data information;
carrying out emotion polarity recognition on the preprocessed public opinion data information by utilizing an ernie3.0 pre-training model so as to identify and mark positive public opinion data information, negative public opinion data information and neutral public opinion data information;
performing topic extraction on the negative public opinion data information;
calculating an explosion index of the number of the extracted topics and public opinion data information associated with the extracted topics in a first preset time period, and carrying out negative public opinion explosion overquick early warning when the explosion index exceeds a first preset threshold;
calculating the emotion indexes of the extracted theme and positive public opinion data information and negative public opinion data information associated with the extracted theme in a second preset time period, and carrying out early warning of excessive negative public opinion fluctuation when the emotion indexes exceed a second preset threshold;
calculating the transmission index of the extracted theme and negative public opinion data information associated with the extracted theme in a third preset time period, and carrying out negative public opinion theme overabundance early warning when the transmission index exceeds a third preset threshold;
calculating the sum of the extracted burst index, emotion index and propagation index of the same topic to obtain a comprehensive negative public opinion index, and carrying out early warning notification on the topic and a corresponding public opinion event when the comprehensive negative public opinion index exceeds a fourth preset threshold.
The further technical scheme is as follows: the calculating of the explosion index of the number of the extracted topics and the public opinion data information associated with the extracted topics within a first preset time period specifically comprises the following steps: according to the formula
Calculating an explosion index EI of the extracted topic and the amount of public opinion data information associated with the extracted topic; wherein (1)>
For the number of negative public opinion data information for which the extracted topic t appears on day i,
the number of negative public opinion data information of the extracted topic t appears for the nth day.
The further technical scheme is as follows: the calculating the emotion indexes of the extracted theme and the positive public opinion data information and the negative public opinion data information associated with the extracted theme in the second preset time period specifically includes: according to the formula
Calculating an emotion index SI of the extracted topic and positive public opinion data information and negative public opinion data information associated with the extracted topic; wherein (1)>
For the number of positive public opinion data information of the subject t extracted for the occurrence on day i,/day->
The number of negative public opinion data information of the extracted topic t appears for the nth day.
The further technical scheme is as follows: the calculating the propagation index of the extracted topic and the negative public opinion data information associated with the extracted topic in a third preset time period specifically includes: according to the formula
Calculating a propagation index of the extracted topic and negative public opinion data information associated with the extracted topic; wherein (1)>
For the number of negative public opinion data information of the extracted topic t occurring on day n,/for the number of negative public opinion data information of the extracted topic t>
The number of negative public opinion data information of the extracted topic t appears for the i-th day.
The further technical scheme is as follows: the early warning notification of the topic and the corresponding public opinion event specifically comprises the following steps: early warning notification is carried out on the theme and the corresponding public opinion event by sending popup window reminding/sending short message/mobile phone micro-message public number sending notification/incoming call conversation.
The further technical scheme is as follows: the extracting the subject of the negative public opinion data information specifically comprises the following steps: and extracting keywords of the negative public opinion data information by adopting a TF-IDF algorithm, wherein each keyword is marked as a theme.
The further technical scheme is as follows: the method comprises the steps of extracting key words of negative public opinion data information by adopting a TF-IDF algorithm, and then further comprising: and displaying weight information corresponding to each keyword.
The further technical scheme is as follows: the values of the first preset threshold, the second preset threshold and the third preset threshold are all 1, and the value of the fourth preset threshold is 2.
The further technical scheme is as follows: the preprocessing of the collected public opinion data information specifically comprises:
deleting unnecessary blank spaces and line feed symbols in the collected public opinion data information;
and/or deleting the @ + user name, the emoticon and the mailbox in the acquired public opinion data information;
and/or canceling the escape HTML mark in the collected public opinion data information;
and/or replacing hyperlinks mentioned in the collected public opinion data information with URLs;
and/or converting the traditional Chinese characters in the collected public opinion data information into simplified Chinese characters.
The beneficial technical effects of the invention are as follows: according to the method, the public opinion data information is collected from the social network platform and preprocessed, the emotion polarity of the preprocessed public opinion data information is identified to identify positive public opinion data information, negative public opinion data information and neutral public opinion data information in the marked public opinion data information, theme extraction is carried out on all negative public opinion data information, further the burst index, emotion index and propagation index of the extracted theme are calculated, and early warning is carried out when the burst index, emotion index and propagation index exceed the set threshold values respectively, the comprehensive public opinion index can be obtained by combining the burst index, emotion index and propagation index, and early warning notification is carried out on the theme and corresponding public opinion events when the comprehensive negative public opinion index exceeds the fourth preset threshold value, so that the method can realize collection, analysis and early warning of mass data of the social network platform, namely can identify negative public opinion events according to the negative public opinion theme, and realize early warning of the public opinion events corresponding to the theme through calculating, threshold value judging and the like on the burst index, emotion index and propagation index of the negative public opinion theme, and can realize early warning of the public opinion event corresponding to be accurately perceived by a network public opinion in advance, and realize the early warning of a public opinion in a first time and early-stage public opinion mechanism against the situation of a public opinion and the public opinion in a public opinion enterprise, and the early warning system is accurately known in the aspect of a public opinion and a public opinion of a public opinion mechanism.
Drawings
Fig. 1 is a flowchart of an embodiment of an internet negative public opinion warning method according to the present invention.
Detailed Description
The present invention will be further described with reference to the drawings and examples below in order to more clearly understand the objects, technical solutions and advantages of the present invention to those skilled in the art.
Referring to fig. 1, fig. 1 is a flowchart of an embodiment of an internet negative public opinion warning method according to the present invention. In the embodiment shown in the drawings, the internet negative public opinion early warning method includes:
s101, collecting public opinion data information from a social network platform, and preprocessing the collected public opinion data information.
In this step, the social network platform includes microblog, bar, news, forum, weChat, digital newspaper, and the like, and in this embodiment, public opinion data information generated in a preset time period by the preset social network platform may be collected, where the public opinion data information includes one or more texts, for example, when the preset social network platform is a microblog, the public opinion data information may include at least one of a post, comment information, and forwarding post information.
Specifically, the preprocessing the collected public opinion data information specifically includes: deleting unnecessary blank spaces and line feed symbols in the collected public opinion data information; and/or deleting the @ + user name, the emoticon and the mailbox in the acquired public opinion data information; and/or canceling the escape HTML mark in the collected public opinion data information; and/or replacing hyperlinks mentioned in the collected public opinion data information with URLs; and/or converting the traditional Chinese characters in the collected public opinion data information into simplified Chinese characters.
S102, carrying out emotion polarity recognition on the preprocessed public opinion data information by utilizing an ernie3.0 pre-training model so as to identify and mark positive public opinion data information, negative public opinion data information and neutral public opinion data information.
In the step, the ernie3.0 model is used for carrying out emotion polarity recognition on the preprocessed public opinion data information, and the public opinion data information which is marked as positive public opinion data information, the public opinion data information which is marked as negative public opinion data information and the public opinion data information which is marked as neutral public opinion data information are recognized and stored according to a time sequence.
S103, extracting the theme of the negative public opinion data information.
In this step, a TF-IDF algorithm (Term Frequency-inverse document Frequency algorithm) is adopted to extract keywords of all negative public opinion data information, each keyword is marked as a topic, and weight information corresponding to each keyword can be displayed, ranking can be performed according to the weight size corresponding to the keyword for a user to view, and the user can view public opinion data information related to the keyword, for example, when the social network platform is a microblog, the total number of posts, the number of negative posts, the percentage of negative posts, the negative posts at a certain time of a certain day, the negative posts searched according to the keyword, and the like related to the keyword can be also viewed.
S104, calculating an explosion index of the number of the extracted topics and public opinion data information associated with the extracted topics in a first preset time period, and carrying out negative public opinion explosion too fast early warning when the explosion index exceeds a first preset threshold.
Preferably, in this step, the first preset threshold is 1.
In the invention, the calculation of the number of extracted topics and public opinion data information associated with the extracted topics is performed at a first preset timeBurst index in interval, specifically including: according to the formula
Calculating an explosion index EI of the extracted topic and the amount of public opinion data information associated with the extracted topic; wherein (1)>
For the number of negative public opinion data information of the subject t extracted for the occurrence on day i,/i>
The number of negative public opinion data information of the extracted topic t appears for the nth day.
Understandably, the first preset time period can be set according to user selection, while Relu is an activation function, also called a linear rectification function, when the numerical value in a bracket of the Relu function is smaller than 0, the result of the activation function becomes 0, when the numerical value is larger than zero, the original numerical value is kept, when EI is larger than or equal to 1, the number of negative public opinion data information of the extracted subject t on the nth day is 2 times as large as the previous n-1 balance average value, the increment degree is 100%, the burst index early warning is triggered, and the negative public opinion burst early warning can be carried out in a mode of sending a popup window prompt/sending a short message/a mobile phone micro-message public signal to send a notice/an incoming call; while when
When the mean value is smaller than the previous n-1 days, the negative emotion public opinion shows negative growth, the Relu activation function is triggered, the EI value is zero, and early warning information is not provided for the burst index.
S105, calculating emotion indexes of the extracted theme and positive public opinion data information and negative public opinion data information associated with the extracted theme in a second preset time period, and carrying out early warning of excessive negative public opinion fluctuation when the emotion indexes exceed a second preset threshold.
In this step, the second preset threshold is 1.
In the invention, the extracted subject matter and the extracted subject matter are calculatedThe emotion indexes of the associated positive public opinion data information and negative public opinion data information in the second preset time period specifically comprise: according to the formula
Calculating an emotion index SI of the extracted topic and positive public opinion data information and negative public opinion data information associated with the extracted topic; wherein (1)>
For the number of positive public opinion data information of the subject t extracted for the occurrence on day i,/day->
The number of negative public opinion data information of the extracted topic t appears for the nth day.
It is understood that when SI is greater than or equal to 1, the ratio of negative public opinion data information and positive public opinion data information of the extracted topic t on the nth day has reached 2 times the mean value of the previous n-1 days, the growth degree reaches 100%, the emotion index early warning is triggered, and when the nth day ratio is smaller than the mean value of the previous n-1 days, the positive emotion public opinion takes the dominant role, the Relu activation function is triggered, the SI value is zero, and early warning information is not provided for the emotion index any more.
S106, calculating the transmission index of the extracted theme and the negative public opinion data information associated with the extracted theme in a third preset time period, and carrying out negative public opinion theme overabundance early warning when the transmission index exceeds a third preset threshold.
In this step, the third preset threshold is 1.
In the invention, the calculating the propagation index of the extracted topic and the negative public opinion data information associated with the extracted topic in the third preset time period specifically includes: according to the formula
Calculating a propagation index of the extracted topic and negative public opinion data information associated with the extracted topic; wherein (1)>
For the number of negative public opinion data information of the extracted topic t occurring on day n,/for the number of negative public opinion data information of the extracted topic t>
The number of negative public opinion data information of the extracted topic t appears for the i-th day.
In this embodiment, the base log may take 10 as the base when using the propagation exponent, and the base may be modified appropriately for larger level data.
S107, calculating the sum of the extracted burst index, emotion index and propagation index of the same topic to obtain a comprehensive negative public opinion index, and carrying out early warning notification on the topic and a corresponding public opinion event when the comprehensive negative public opinion index exceeds a fourth preset threshold.
In this step, the comprehensive negative public opinion index POI is obtained through calculation according to the formula poi=si+ei+di, and the fourth preset threshold is preferably 2.
Understandably, the internet negative public opinion warning method of the invention can be operated in an app carried in a terminal device (such as a mobile phone, a pad, etc.), and interaction between a user and a system can be realized through the app.
In summary, it can be known that by collecting public opinion data information from a social network platform and preprocessing the public opinion data information, and carrying out emotion polarity recognition on the preprocessed public opinion data information to identify positive public opinion data information, negative public opinion data information and neutral public opinion data information in the marked public opinion data information, extracting topics from all negative public opinion data information, further calculating burst indexes, emotion indexes and propagation indexes of the extracted topics, carrying out early warning when the burst indexes, emotion indexes and propagation indexes respectively exceed the set threshold values, and also combining the burst indexes, emotion indexes and propagation indexes to obtain comprehensive negative public opinion indexes, and carrying out early warning notification on the topics and corresponding public opinion events when the comprehensive negative public opinion indexes exceed the fourth preset threshold value, the invention can identify negative public opinion events according to the public opinion topics by carrying out emotion polarity recognition and topic extraction on the public opinion data information, and then realizing early warning on the three dimensions and the negative public opinion indexes corresponding to the topics, thereby realizing accurate and early warning of the public opinion in the early warning network for the public opinion in advance of the first time, and realizing the early warning of the public opinion in response to the public opinion of the public opinion enterprises, and the early warning system, and the invention can realize accurate early warning of the public opinion information at the early warning source.
The foregoing is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Various equivalent changes and modifications can be made by those skilled in the art based on the above embodiments, and all equivalent changes or modifications made within the scope of the claims shall fall within the scope of the present invention.
Claims (9)
1. An internet negative public opinion early warning method is characterized by comprising the following steps:
collecting public opinion data information from a social network platform, and preprocessing the collected public opinion data information;
carrying out emotion polarity recognition on the preprocessed public opinion data information by utilizing an ernie3.0 pre-training model so as to identify and mark positive public opinion data information, negative public opinion data information and neutral public opinion data information;
performing topic extraction on the negative public opinion data information;
calculating an explosion index of the number of the extracted topics and public opinion data information associated with the extracted topics in a first preset time period, and carrying out negative public opinion explosion overquick early warning when the explosion index exceeds a first preset threshold;
calculating the emotion indexes of the extracted theme and positive public opinion data information and negative public opinion data information associated with the extracted theme in a second preset time period, and carrying out early warning of excessive negative public opinion fluctuation when the emotion indexes exceed a second preset threshold;
calculating the transmission index of the extracted theme and negative public opinion data information associated with the extracted theme in a third preset time period, and carrying out negative public opinion theme overabundance early warning when the transmission index exceeds a third preset threshold;
calculating the sum of the extracted burst index, emotion index and propagation index of the same topic to obtain a comprehensive negative public opinion index, and carrying out early warning notification on the topic and a corresponding public opinion event when the comprehensive negative public opinion index exceeds a fourth preset threshold.
2. The internet negative public opinion warning method of claim 1, wherein the calculating the burst index of the extracted topic and the number of public opinion data information associated with the extracted topic within a first preset time period specifically comprises: according to the formula
Calculating an explosion index EI of the extracted topic and the amount of public opinion data information associated with the extracted topic; wherein (1)>
For the number of negative public opinion data information of the subject t extracted for the occurrence on day i,/i>
The number of negative public opinion data information of the extracted topic t appears for the nth day.
3. The internet negative public opinion warning method of claim 1, wherein the calculating the extracted topic and the emotion indexes of the positive public opinion data information and the negative public opinion data information associated with the extracted topic within the second preset time period specifically comprises: according to the formula
Calculating an emotion index SI of the extracted topic and positive public opinion data information and negative public opinion data information associated with the extracted topic; wherein (1)>
For the number of positive public opinion data information of the subject t extracted for the occurrence on day i,/day->
The number of negative public opinion data information of the extracted topic t appears for the nth day.
4. The internet negative public opinion warning method of claim 1, wherein the calculating the propagation index of the extracted topic and the negative public opinion data information associated with the extracted topic within the third preset time period specifically includes: according to the formula
Calculating a propagation index of the extracted topic and negative public opinion data information associated with the extracted topic; wherein (1)>
For the number of negative public opinion data information of the extracted topic t occurring on day n,/for the number of negative public opinion data information of the extracted topic t>
The number of negative public opinion data information of the extracted topic t appears for the i-th day.
5. The internet negative public opinion warning method of claim 1, wherein the early warning notification of the topic and the corresponding public opinion event specifically comprises: early warning notification is carried out on the theme and the corresponding public opinion event by sending popup window reminding/sending short message/mobile phone micro-message public number sending notification/incoming call conversation.
6. The internet negative public opinion warning method of claim 1, wherein the extracting the subject of the negative public opinion data information specifically comprises: and extracting keywords of the negative public opinion data information by adopting a TF-IDF algorithm, wherein each keyword is marked as a theme.
7. The internet negative public opinion warning method of claim 6, wherein the method further comprises the steps of: and displaying weight information corresponding to each keyword.
8. The internet negative public opinion warning method of claim 1, wherein the values of the first preset threshold, the second preset threshold and the third preset threshold are all 1, and the value of the fourth preset threshold is 2.
9. The internet negative public opinion warning method of claim 1, wherein the preprocessing of the collected public opinion data information specifically comprises:
deleting unnecessary blank spaces and line feed symbols in the collected public opinion data information;
and/or deleting the @ + user name, the emoticon and the mailbox in the acquired public opinion data information;
and/or canceling the escape HTML mark in the collected public opinion data information;
and/or replacing hyperlinks mentioned in the collected public opinion data information with URLs;
and/or converting the traditional Chinese characters in the collected public opinion data information into simplified Chinese characters.
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| CN117743581A (en) * | 2023-12-26 | 2024-03-22 | 中国农业科学院农业信息研究所 | Intervention method for agricultural product quality safety network rumors |
| CN117743581B (en) * | 2023-12-26 | 2024-06-11 | 中国农业科学院农业信息研究所 | Intervention method for agricultural product quality safety network rumors |
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