Method for microblog hot event online detection based on emotion analysis

Abstract

The invention discloses a method for microblog hot event online detection based on emotion analysis. According to the method for microblog hot event online detection based on emotion analysis, emotion extraction is conducted on online microblog texts according to emotion analysis, the bursting state of emotions and emotion texts is detected according to the improved Kleinberg algorithm, hot topics are extracted according to an affinity propagation clustering algorithm in the bursting period, so that only a small part of texts with a large amount of effective information participate in event extraction, the data volume is reduced, meanwhile a large amount of data noise is filtered out, and therefore the purpose that online real-time detection of the microblog hot events is achieved.

Description

technical field [0001] The invention belongs to the technical field of mobile Internet, and in particular relates to a method for online detection of microblog hotspot events based on sentiment analysis. Background technique [0002] The Internet is gradually evolving into a ubiquitous computing platform and information dissemination platform. The emergence and rapid development of social network applications such as online social networking sites, microblogs, blogs, forums, and wikis have brought about profound changes in the way humans use the Internet—by Simple information search and web browsing turn to the construction and maintenance of social relationships on the Internet and the creation, exchange and sharing of information based on social relationships. [0003] At present, social network applications are in a period of vigorous development. Since its launch 8 years ago, Facebook has more than 1 billion users, making it the third most populous country. The number of...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the low efficiency of existing event detection methods in massive online microblog text data streams, the present invention provides a method for online detection of microblog hot events based on sentiment analysis, which extracts emotions from online microblog texts through sentiment analysis, The improved Kleinberg algorithm is used to detect the burst state of emotion and emotional text, and during the burst period, the nearest neighbor propagation clustering algorithm is used to extract hot topics, so that only a small number of effective texts with a relatively large amount of information participate in event mining. A large amount of data noise is filtered out at the same time, so that online real-time detection of microblog hot events can be realized

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