Method for identifying microblog key users based on improved Page Rank

Abstract

The invention discloses a method for identifying microblog key users based on an improved Page Rank. The method comprises the steps that microblog information data are input, wherein the microblog information data comprise n microblogs; word segmentation is conducted on texts of the n microblogs; according to a word segmentation result, a reverse index structure is established, so that retrieval is conveniently conducted according to appointed keywords; according to the retrieved relevant microblog, forwarding hierarchy information of the microblog is extracted and a weighting directed graph is established, wherein the weighting directed graph is a forwarding network G; the forwarding network G is divided into a plurality of maximum connected subgraphs Gi; the Page rank algorithm is applied to each sub network Gi according to the parallelization computing technology; computing results of the sub networks are combined, so that ranking results of the whole network G are generated; the first m ranking results of the ranking results are selected, serve as the key users and are output. According to the method for identifying the microblog key users based on the improved Page Rank, the parallelization computing technology is adopted, a dynamic forwarding network of a microblog platform is ranked and computed in a big data environment, so that the key users in the information transmission process are identified, and the method is applied to the fields of network public opinion analysis and the like.

Description

technical field [0001] The invention relates to a microblog key user identification method, in particular to an improved PageRank-based microblog key user identification method, which belongs to the field of complex network and data mining, and is especially aimed at analyzing massive microblog data. Background technique [0002] The key users of the Weibo platform are those who play an important role in the dissemination and diffusion of information. Key users play an important intermediary or filtering role in the formation of mass communication effects. They spread information to the audience and form a cascading dissemination of information. Therefore, the identification of key users plays an important role in information discovery and dissemination analysis, and has great guiding significance for network public opinion analysis and other work. However, content-based key user identification is often not accurate enough due to the characteristics of short texts on Weibo;...

AI Technical Summary

Problems solved by technology

In addition, considering that the Weibo platform has the characteristics of massive data, the dynamically generated network is often huge in scale and requires instant calculation results. Therefore, the traditional power iteration algorithm can hardly meet the demand in terms of calculation time and space.

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