A microblog hot word and hot topic mining system and method

Abstract

The invention relates to the technical field of social networks, in particular to a micro-blog hot word and hot topic mining system and method. The method includes the following steps that content data released in a micro-blog are preprocessed to acquire a candidate hot word sequence; according to the frequency of occurrence and suddenness of candidate hot words in a candidate hot word set at the current moment and in a given historical time window, the vitality of each candidate hot word is worked out, and a hot word set is formed by screening the candidate hot words; according to the hot word set formed by screening the candidate hot words, hot word correlation is worked out, and a hot word co-occurrence network is constructed; according to the hot word co-occurrence network, the hot word set is partitioned through the hot word clustering algorithm based on multi-label propagation to acquire a hot topic set. By means of the micro-blog hot word and hot topic mining system and method, efficient micro-blog hot word and hot topic mining is achieved, and mining precision and processing efficiency are improved.

Description

technical field [0001] The invention relates to the technical field of social network, in particular to a microblog hot word and hot topic mining system and method. Background technique [0002] With the rise of Weibo, people's participation is constantly increasing. Users can publish what they see and hear anytime and anywhere through computers and mobile phones, and realize instant sharing. Now Weibo has become a fashion on the Internet, and it is also an important place for generating and discussing hot topics. Hot topics refer to topics that frequently appear on the Internet within a period of time and are widely concerned and discussed by people. The exponential growth of microblog information makes how to effectively control massive amounts of information and extract hot topics become an urgent problem to be solved. [0003] For hot topic detection, the traditional method is to cluster the text, but this method is not conducive to the user's intuitive identification o...

AI Technical Summary

Problems solved by technology

[0006] For the hotspot detection problem of massive microblog data, the main problems of the existing hotword clustering methods are: firstly, the words involved in different topics in the clustering results are not allowed to overlap, which is not consistent with the actual situation, and it is easy to As a result, some topics have not been discovered, or the recognition of topics is very low

In addition, the traditional clustering algorithm has a high time complexity, and it is difficult to adapt to the clustering requirements of massive microblog data.

[0007] In summary, there have been relatively complete technologies and methods for the influence analysis of individual users in social networks, but there are relatively few methods for community-level influence analysis in social networks, and there is a lack of analysis of communities in social networks. Comprehensive analysis and evaluation of influence, in the face of large-scale social network scenarios, existing methods are difficult to meet the requirements in terms of analysis effect and efficiency

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