A social network user abnormity detection method and system based on an association map

An anomaly detection and social network technology, applied in the direction of network data retrieval, website content management, data processing applications, etc., can solve the problems of weak correlation and difficult user anomaly detection, and achieve the effect of easy anomaly detection and close association

Active Publication Date: 2019-05-31
INST OF COMPUTING TECH CHINESE ACAD OF SCI +1
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AI Technical Summary

Problems solved by technology

[0008] The present invention mainly aims at the shortcomings of the existing event visualization display technology and the weak correlation of various entities such as events, users, and event topics, which makes it difficult to detect user anomalies. Various entities such as event topics build heterogeneous association network graphs for user anomaly detection; without missing event information, users can understand the development and evolution of the entire event more comprehensively and in-depth, and according to the existing heterogeneous association network Graph is more intuitive for user anomaly detection

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  • A social network user abnormity detection method and system based on an association map
  • A social network user abnormity detection method and system based on an association map
  • A social network user abnormity detection method and system based on an association map

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Embodiment Construction

[0048] Specifically, the invention discloses a social network user anomaly detection method based on an association graph, which includes

[0049] Step 1. Obtain the keyword, extract multiple social data with the keyword in the social network platform, collect the social data as an event corresponding to the keyword and store it in the event database, and according to the basic information of the publisher of the social data, Establish a user database, and establish an event dissemination database based on the forwarding chain and comment chain of the social data;

[0050] Step 2. Perform clustering processing on the social data corresponding to the event to obtain the subtopic of the event, collect the subtopics in chronological order, and obtain a temporally continuous event cluster subset;

[0051] Step 3. Obtain users who participate in social data publishing in the event database as publishing users. According to the association between the publishing user and the event, ...

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Abstract

The invention relates to a social network user abnormity detection method and system based on an association map. Aiming at the defects of the existing event visualization display technology and the weakness of relevance of various entities such as events, users and event topics, the invention provides an event visualization method based on a microblog platform, and the heterogeneous association network map is constructed by various entities such as the events, the users and the event topics to carry out user anomaly detection; While the event information is not missed, the user can more comprehensively and deeply know the development evolution process of the whole event, and user abnormity detection can be more visually carried out according to the existing heterogeneous association network map.

Description

technical field [0001] The invention relates to the field of heterogeneous network graphs of network events in social network propagation and user anomaly detection, and in particular to a method and system for detecting social network user anomalies based on correlation graphs. Background technique [0002] With the rapid development of the Internet, various social media have emerged in recent years, such as Facebook, Twitter, Sina Weibo, and Renren.com. Among them, the Weibo platform represented by Twitter and Sina Weibo has become a popular Internet application due to its open information sharing and dissemination characteristics. [0003] Microblog, short for Microblog, users can publish text, pictures, videos and other information within 140 characters anytime and anywhere on the platform. Weibo has the characteristics of originality, timeliness, fragmentation and repetition. In the microblog platform, users can search and view topics they are interested in, browse to...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/906G06F16/958G06Q50/00
Inventor 曹娟郭俊波谢添刘春阳陈志鹏张旭王鹏张翔宇
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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