Network public opinion analysis processing method based on deep learning

Abstract

The invention relates to the technical field of public opinion analysis and processing, in particular to a network public opinion analysis and processing method based on deep learning, which comprises the following steps: S1, a user logs in through a user side, completes account registration after information filling and identity verification, and then sends an event to an operation module through an input unit; the operation module transmits the event data to the first transmission unit; s2, the first transmission unit transmits the data to a second transmission unit in the public opinion platform, the second transmission unit transmits the event data to an analysis processing module, the analysis processing module analyzes and processes the event data and then filters negative public opinion data, and after the event is processed by the analysis processing module, the event data is transmitted to the second transmission unit; the public opinion data is analyzed and processed before the display module in the public opinion platform displays the public opinion data, so that the display content of the public opinion platform can be controlled, and negative public opinions are prevented from guiding social guidance to cause adverse effects on the society and victims.

Description

Technical Field

[0001] The present invention relates to the technical field of public opinion analysis and processing, and in particular to a network public opinion analysis and processing method based on deep learning. Background Art

[0002] Online public opinion refers to the public opinions and emotional tendencies that emerge on the Internet related to specific events, topics or individuals. Online public opinion can be spread and formed through social media, news websites, forums, Weibo and other channels. Online public opinion has the characteristics of wide participation and fast spread, which can quickly attract widespread attention and influence public opinion. Online public opinion can be spread and expressed on a variety of platforms, including social media platforms, news websites, forums and communities, video sharing platforms and instant communication tools. These platforms provide users with space to freely express their opinions and views, and have become an important medium for the dissemination and exchange of online public opinion.

[0003] The current manifestations of online public opinion are complex and intricate, among which the existence and behavior of keyboard warriors often cause a series of negative impacts on individuals, organizations and society. Keyboard warriors often use anonymity and virtual identities to publish insults, malicious attacks and even personal insults through online public opinion platforms. This behavior not only harms the reputation and dignity of individuals, but also threatens social order and morality. Some keyboard warriors may publish defamatory remarks and personal attacks on the Internet, causing damage to the reputation and privacy of others. Such attacks may cause individuals, organizations or brands to be harmed by public opinion, and even cause psychological pain to the victims. Therefore, it is very necessary to analyze and process online public opinion in order to control the direction of online public opinion.

[0004] In view of this, in order to overcome the above-mentioned technical problems, the present invention proposes a network public opinion analysis and processing method based on deep learning, which solves the above-mentioned technical problems. Summary of the invention

[0005] In order to make up for the shortcomings of the prior art, the present invention proposes a method for analyzing and processing online public opinion based on deep learning. By analyzing and processing the public opinion data before displaying it in the display module of the public opinion platform, the display content of the public opinion platform can be controlled to avoid negative public opinion guiding the social orientation and causing adverse effects on society and victims.

[0006] The present invention provides a method for analyzing and processing network public opinion based on deep learning, comprising the following steps: S1: The user logs in through the user terminal and completes the account registration after filling in the information and identity verification, and then sends the event to the operation module through the input unit, and the operation module transmits the event data to the first transmission unit; S2: The first transmission unit transmits the data to the second transmission unit in the public opinion platform, and the second transmission unit transmits the event data to the analysis and processing module. After the analysis and processing module analyzes and processes the event data, it filters the negative public opinion data. After the event is processed by the analysis and processing module, it transmits the event to the display module for display; S3: The display module transmits the display result to the second transmission unit, then transmits it to the first transmission unit along the second transmission unit, and finally transmits it to the viewing unit in the operation module along the first transmission unit for viewing; S4: The viewing unit can view the public opinion data of the display module in the public opinion platform and express opinions. The user will transmit the comment data to the operation module through the input unit, and then the operation module will transmit it to the first transmission unit, and finally transmit it to the analysis and processing module along the second transmission unit for analysis and processing, and finally transmit it to the display module for data update and display.

[0007] Preferably, the user terminal includes a first transmission unit and an operation module; the operation module includes a viewing unit and an input unit; the input unit transmits the public opinion material or public opinion speech to the first transmission unit through the operation module; The public opinion platform includes a second transmission unit, an analysis and processing module and a display module; the second transmission unit is connected to the first transmission unit, and is used to transmit the data of the first transmission unit to the analysis and processing module for analysis, and the analysis and processing module transmits the data to the display module for display after analysis, and the display module will transmit the displayed data back to the viewing unit in the operation module through the second transmission unit and the first transmission unit for viewing.

[0008] Preferably, the analysis and processing module includes an extraction unit, an identification unit and an export unit; the extraction unit can extract key data from the data; the identification unit can identify negative data in the key data; and the export unit exports the data after clearing it after identification.

[0009] Preferably, the data extracted by the extraction unit includes text, audio and images; the audio and images extracted by the extraction unit are converted into text information.

[0010] Preferably, the analysis and processing module also includes a reference unit; the reference unit forms a database with negative public opinion as a subset; and the identification unit compares the data extracted by the extraction unit with the database in the reference unit.

[0011] Preferably, the analysis and processing module also includes a recording unit and a warning unit; the recording unit can record the source IP address of the negative data identified by the identification unit; the warning unit returns data and warns after the IP address of the source of the negative data increases to a threshold.

[0012] Preferably, the analysis and processing module also includes an analysis unit; the analysis unit monitors and analyzes the data of the same IP address of the recording unit to form a public opinion trend; the warning unit stops warning after the public opinion trend of the data at the same IP address turns toward a positive energy direction.

[0013] Preferably, the analysis and processing module further includes an interception unit; the interception unit intercepts data of the IP address after the IP address of the negative data source exceeds a threshold.

[0014] The beneficial effects of the present invention are as follows: 1. The present invention analyzes and processes the public opinion data before displaying it in the display module of the public opinion platform, thereby being able to control the display content of the public opinion platform, avoiding negative public opinion from guiding the social orientation and causing adverse effects on the society and the victims.

[0015] 2. The present invention purifies and exports the data after removing the negative energy data through the export unit. The purified and exported data will be transmitted to the display module for display, thereby completing the data analysis and processing process. By analyzing and processing the data, the negative public opinion data is further controlled so that the amount of negative public opinion data does not exceed the standard value.

[0016] 3. In the present invention, when the public opinion trend is developing in a positive direction, the warning unit will stop warning the IP address. In this way, the warning unit in the analysis and processing module can supervise and control the user's speech, suppress the spread of negative public opinion, and enable public opinion to develop in a positive direction. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention is further described below in conjunction with the accompanying drawings and implementation modes.

[0018] Figure 1 is a flow chart of the method of the present invention; Figure 2 It is a flowchart of the system in the present invention. DETAILED DESCRIPTION

[0019] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0020] like Figure 1-2 As shown, the present invention includes the following embodiments: Embodiment 1, a method for analyzing and processing network public opinion based on deep learning, comprising the following steps: S1: The user logs in through the user terminal and completes the account registration after filling in the information and identity verification, and then sends the event to the operation module through the input unit, and the operation module transmits the event data to the first transmission unit; S2: The first transmission unit transmits the data to the second transmission unit in the public opinion platform, and the second transmission unit transmits the event data to the analysis and processing module. After the analysis and processing module analyzes and processes the event data, it filters the negative public opinion data. After the event is processed by the analysis and processing module, it transmits the event to the display module for display; S3: The display module transmits the display result to the second transmission unit, then transmits it to the first transmission unit along the second transmission unit, and finally transmits it to the viewing unit in the operation module along the first transmission unit for viewing; S4: The viewing unit can view the public opinion data of the display module in the public opinion platform and express opinions. The user will transmit the comment data to the operation module through the input unit, and then the operation module will transmit it to the first transmission unit, and finally transmit it to the analysis and processing module along the second transmission unit for analysis and processing, and finally transmit it to the display module for data update and display.

[0021] In this embodiment, the user terminal includes a first transmission unit and an operation module; the operation module includes a viewing unit and an input unit; the input unit transmits the public opinion material or public opinion speech to the first transmission unit through the operation module; The public opinion platform includes a second transmission unit, an analysis and processing module, and a display module; the second transmission unit is connected to the first transmission unit, and is used to transmit the data of the first transmission unit to the analysis and processing module for analysis, and the analysis and processing module transmits the data to the display module for display after analysis, and the display module transmits the displayed data back to the viewing unit in the operation module through the second transmission unit and the first transmission unit for viewing; When in use, the user logs in through the user terminal and completes the account registration after filling in the information and identity verification. Then, the event is sent to the operation module through the input unit in the form of text, voice, picture and video. The operation module will transmit the event data to the first transmission unit, and the first transmission unit will transmit the data to the second transmission unit in the public opinion platform. The user terminal is connected to the public opinion platform through the network. After the event data is transmitted to the second transmission unit, the second transmission unit will transmit the event data to the analysis and processing module. After the analysis and processing module analyzes and processes the event data, it will filter the negative public opinion data. After the event is processed by the analysis and processing module, it will be transmitted to the display module for display. The display module will transmit the display result to the second transmission unit, and then transmit it to the first transmission unit along the second transmission unit, and finally transmit it to the viewing unit in the operation module along the first transmission unit for viewing. The viewing unit can view the public opinion data of the display module in the public opinion platform and express opinions. The user will transmit the comment data to the operation module through the input unit, and then transmit it to the first transmission unit by the operation module, and finally transmit it to the analysis and processing module along the second transmission unit for analysis and processing, and finally transmit it to the display module for data update and display. The present invention analyzes and processes the public opinion data before displaying it in a display module in the public opinion platform, thereby being able to control the display content of the public opinion platform, thereby avoiding negative public opinion from guiding the social orientation and causing adverse effects on the society and the victims.

[0022] Embodiment 2; The analysis and processing module includes an extraction unit, an identification unit and an export unit; the extraction unit is capable of extracting key data from the data; the identification unit is capable of identifying negative data in the key data; the export unit exports the data after clearing it after identification.

[0023] In this embodiment, the data extracted by the extraction unit includes text, audio and image; the audio and image extracted by the extraction unit are converted into text information.

[0024] In this embodiment, the analysis and processing module further includes a reference unit; the reference unit forms a database with negative public opinion as a subset; the identification unit compares the data extracted by the extraction unit with the database in the reference unit; When in use, the second transmission unit transmits the event data and comment data to the analysis and processing module, the extraction unit extracts the event data and comment data, the extraction unit converts the audio and image data into text information, which is convenient for the subsequent recognition unit to recognize, and the recognition unit compares the extracted text data with the data in the reference unit to obtain a similarity value. The higher the similarity value, the higher the negative energy data, and vice versa. When the similarity value is lower than a preset threshold, it means that the display standard is met. In this way, the export unit purifies and exports the data after removing the negative energy data. The purified and exported data will be transmitted to the display module for display, thus completing the data analysis and processing process. By analyzing and processing the data, the negative public opinion data is further controlled so that the amount of negative public opinion data does not exceed the standard value.

[0025] Embodiment 3; the analysis and processing module also includes a recording unit and a warning unit; the recording unit can record the source IP address of the negative data identified by the identification unit; the warning unit returns data and warns after the IP address of the source of the negative data increases to a threshold.

[0026] In this embodiment, the analysis and processing module also includes an analysis unit; the analysis unit monitors and analyzes the data of the same IP address of the recording unit to form a public opinion trend; the warning unit stops warning after the public opinion trend of the data at the same IP address turns toward a positive energy direction.

[0027] In this embodiment, the analysis and processing module further includes an interception unit; the interception unit intercepts data of the IP address after the IP address of the negative data source exceeds a threshold; When in use, after the second transmission unit transmits the data to the analysis and processing module, the data is extracted by the extraction unit and identified by the identification unit. The recording unit will record the source IP address of the negative data identified by the identification unit, and perform data statistics and analysis on the IP address. When the same IP address approaches the threshold, the warning unit will send a warning message, and the warning message will be transmitted along the second transmission unit and the first transmission unit to the viewing unit in the operation module to be viewed by the user. When the analysis unit analyzes that the user sends negative data after receiving the warning, and the negative data exceeds the threshold, the interception unit will intercept any data sent by the IP address. When the analysis unit analyzes that the user sends positive data after receiving the warning from the warning unit, and the trend of public opinion is developing in a positive direction, the warning unit will stop warning the IP address. In this way, the warning unit in the analysis and processing module can supervise and control the user's speech, suppress the spread of negative public opinion, and enable public opinion to develop in a positive direction.

[0028] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for analyzing and processing network public opinion based on deep learning, characterized in that: The following steps are involved: S1: The user logs in through the user terminal and completes the account registration after filling in the information and identity verification, and then sends the event to the operation module through the input unit, and the operation module transmits the event data to the first transmission unit; S2: The first transmission unit transmits the data to the second transmission unit in the public opinion platform, and the second transmission unit transmits the event data to the analysis and processing module. After the analysis and processing module analyzes and processes the event data, it filters the negative public opinion data. After the event is processed by the analysis and processing module, it transmits the event to the display module for display; S3: The display module transmits the display result to the second transmission unit, then transmits it to the first transmission unit along the second transmission unit, and finally transmits it to the viewing unit in the operation module along the first transmission unit for viewing; S4: The viewing unit can view the public opinion data of the display module in the public opinion platform and express opinions. The user will transmit the comment data to the operation module through the input unit, and then the operation module will transmit it to the first transmission unit, and finally transmit it to the analysis and processing module along the second transmission unit for analysis and processing, and finally transmit it to the display module for data update and display.

2. According to the method for analyzing and processing network public opinion based on deep learning according to claim 1, it is characterized by: The user terminal includes a first transmission unit and an operation module; the operation module includes a viewing unit and an input unit; the input unit transmits public opinion materials or public opinion comments to the first transmission unit through the operation module; The public opinion platform includes a second transmission unit, an analysis and processing module and a display module; the second transmission unit is connected to the first transmission unit, and is used to transmit the data of the first transmission unit to the analysis and processing module for analysis, and the analysis and processing module transmits the data to the display module for display after analysis, and the display module will transmit the displayed data back to the viewing unit in the operation module through the second transmission unit and the first transmission unit for viewing.

3. According to claim 2, a method for analyzing and processing network public opinion based on deep learning is characterized in that: The analysis and processing module includes an extraction unit, an identification unit and a derivation unit; the extraction unit can extract key data from the data; the identification unit can identify negative data in the key data; The export unit exports the data after clearing the data through identification.

4. According to claim 3, a method for analyzing and processing network public opinion based on deep learning is characterized in that: The data extracted by the extraction unit includes text, audio and image; the audio and image extracted by the extraction unit are converted into text information.

5. According to claim 4, a method for analyzing and processing network public opinion based on deep learning is characterized in that: The analysis and processing module also includes a reference unit; the reference unit forms a database with negative public opinion as a subset; the identification unit compares the data extracted by the extraction unit with the database in the reference unit.

6. According to claim 3, a method for analyzing and processing network public opinion based on deep learning is characterized in that: The analysis and processing module also includes a recording unit and a warning unit; the recording unit can record the source IP address of the negative data identified by the identification unit; the warning unit returns data and warns after the IP address of the source of the negative data increases to a threshold.

7. The method for analyzing and processing network public opinion based on deep learning according to claim 6 is characterized in that: The analysis and processing module also includes an analysis unit; the analysis unit monitors and analyzes the data of the same IP address of the recording unit to form a public opinion trend; the warning unit stops warning after the public opinion trend of the data of the same IP address turns toward a positive energy direction.

8. The method for analyzing and processing network public opinion based on deep learning according to claim 7 is characterized in that: The analysis and processing module also includes an interception unit; the interception unit intercepts data of the IP address after the IP address of the negative data source exceeds a threshold.

Images