Event Evolution Analysis in Microblogging Based on a View of Public Opinion Field

Abstract

Event evolution analysis, which focus on discovering underlying relationships among events by using methods of data mining on text corpus, is a meaningful and challenge problem. In recent years, more and more people began to express their opinion on public events though microblogging services. It makes that the microblogging corpus contains not only the facts related to the events, but also the public concerns. Therefore, we believe that the event evolution analysis in microblogging should take different approaches and perspectives with the state-of-the-arts. In this paper, we employ the concept of public opinion field, on which event information and public opinion in text corpus are distinguished. Based on this view, we focus on how does the public opinion affect the evolution of events, propose a method to measure the influence, and represent it on the event evolution graph. The preliminary experiments on our dataset about H7N9 bird flu collected from Weibo shows that our method can get consistent results with our intuitive feel, that illustrates the effectiveness of the method.

Exploring Social Relationships in Text Streams

“…Deng et al distinguished event information and public opinion in text corpus. They tracked the evolution of public concern which they believed is a reflection of corresponding events in social media data [18] and analysed the event evolution from the view of opinion field [19], however the authors failed to predict the future evolution of detected events.…”

Semantic Outbreak Power Based Evolution of Web Event in Large-Scale Ubiquitous Contexts

“…It contained three stages: document preprocessing, threshold-resilient document classification, and adaptive splitting document clustering. Deng and Xu [35] propose a method to measure the influence and represent the event evolution graph. Lee et al [36] proposed an incremental tracking framework for cluster evolution over highly dynamic networks.…”