Micro blog network opinion leader identification method

Abstract

The invention discloses a micro blog network opinion leader identification method and is used for solving the technical problem of poor recall rate of the existing opinion leader identification method. The technical scheme includes storing network topology information collected from the internet into a database by using a web crawler tool; constructing a directed network diagram G=(V, E); calculating an effective fan collection Ef (u); calculating a node weight IRL (ui) generated by a link relationship; calculating a node weight IRTR (ui) generated by a node interactive relationship; calculating a node comprehensive weight IR (ui); and calculating comprehensive weights of all nodes in the network diagram, performing sequencing in a descending order according to the comprehensive weights, and selecting n nodes with larger comprehensive weights as candidates of opinion leaders. The fan number possessed by the nodes, factors such as the node link relationship and the interactive relationship are considered when the node weights are calculated, so that the recall rate and the accuracy are improved. Through detection, the return rate is improved from 81.7-88.5% of the background technology to above 89.3%, and the accuracy is improved from 84.7-90.4% of the background technology to above 91.7%.

Description

technical field [0001] The invention relates to an identification method, in particular to an identification method for microblog network opinion leaders. Background technique [0002] With the development of Web2.0 technology, some new types of network applications have emerged on the Internet, such as social networks, microblog networks, etc., showing increasing value and influence in information dissemination and interpersonal relationship carrying. [0003] As an extension of real social networks on the Internet, social networks aim to help people establish and maintain interpersonal networks more effectively. Different from websites characterized by aggregation of information, social networks are characterized by aggregation of people. People can establish and maintain their own circle of friends through social networks, becoming a new type of personal social interaction and information exchange platform. The information dissemination mode accelerates the dissemination...

AI Technical Summary

Problems solved by technology

[0008] Document 1 "Discovering Important Bloggers based on Analyzing Blog Threads [WWW, Chiba, Japan, May 10-14, 2005]" proposes an important blog user analysis method ThreadRank based on post content analysis, which analyzes a large number of blog content To judge the importance of its users, it takes a lot of time for content cleaning and analysis, and the efficiency is low

[0009] Document 2 "Identifying Opinion Leaders in the Blogosphere [CIKM, pp.971-974, 2007]" proposes an opinion leader identification method InfluenceRank, which judges the importance of users based on comparison with other blogs, and how these users contribute to The contribution made by the entire network is used to calculate user weights, and the cosine theorem is used to calculate the similarity of different blog entities, which is complex and expensive

[0010] Document 3 "TwitterRank: Finding topic-sensitive Inuential Twitterers [WSDM, 2010]" proposed a Twitter network node calculation method TwitterRank, which is based on the user relationship in Twitter, the distribution between fans and followers, and the information dissemination The role played by various user groups in the process is used for weight calculation. This algorithm is mainly based on topic analysis, and the recall rate is not high.

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