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User activity type identification method based on social media

A user activity and type identification technology, applied in the field of user activity type identification based on social media, can solve the problems of low classification accuracy, ignore structural information and users in comments, and achieve the effect of improving recognition accuracy

Active Publication Date: 2020-05-22
CHINA UNIV OF GEOSCIENCES (WUHAN)
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AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is that in the above-mentioned current traditional social media-based activity type identification method, only the text information of comments is considered separately, and the structural information between comments and the influence of users are ignored, resulting in low classification accuracy. technical problems, provide a social media-based user activity type identification method to solve the above technical defects

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  • User activity type identification method based on social media
  • User activity type identification method based on social media
  • User activity type identification method based on social media

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Embodiment Construction

[0024] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, the specific implementation manners of the present invention will now be described in detail with reference to the accompanying drawings.

[0025] A method for identifying user activity types based on social media, such as figure 1 shown, including:

[0026] S1. Crawl comment data representing different activity types on the Yelp website, and add a category label of user activity type to each comment data crawled;

[0027] S2. Record the ID information of each user and the friend relationship information between each user, and the friend relationship information is used to represent whether they are friends;

[0028] S3. Perform data preprocessing on the comment data to filter out useless information;

[0029] S4, using a language model (such as tfidf), the comment data of the text type (comment of the whole sentence or the whole paragraph), the user ID, ...

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Abstract

The invention provides a user activity type identification method based on social media. Generally, a graph is composed of nodes and edges. The method comprises the following steps: firstly, taking all user comments and words forming the comments as a plurality of nodes in the graph, and defining weights and relationships of edges between different words and between words and comments to form a most basic graph; secondly, regarding the users who make comments as another type of nodes, defining the weights of the users and the edges between the comments according to the publishing relation between the users and the comments, and adding user nodes into the formed graph; then other friends of the user who makes the comments are regarded as nodes of a new class, relation weights between the user and the friend nodes corresponding to the user are defined, and a large graph containing text information and structure information of the comments is formed; and finally, performing node classification on the formed large graph by utilizing a graph convolution network to obtain the accuracy of user activity classification.

Description

technical field [0001] The invention belongs to the technical field of sentiment classification of comment data, and in particular relates to a method for identifying user activity types based on social media. Background technique [0002] User activity type recognition is a very important research problem in many fields. Not only has great academic research significance, but also has extensive commercial application value. In terms of intelligent transportation, a large-scale, comprehensive, real-time, accurate and efficient integrated transportation management system can be established. At the same time, in terms of advertisement recommendation, it can provide various users with objective and professional knowledge assistance and product filtering information, and provide merchants with consumers' choice intentions. If multiple activity states of a user are analyzed within a period of time, it is possible to infer the transition of the user's activity state and the chang...

Claims

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Application Information

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IPC IPC(8): G06F16/951G06F16/958G06N3/08
CPCG06F16/951G06F16/958G06N3/08
Inventor 李润佳姚宏程亚凡王晨威李兵
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)
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