Hot topic detection in local areas using Twitter and Wikipedia

Shota Ishikawa, Yutaka Arakawa, Shigeaki Tagashira, Akira Fukuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

As microblog services become increasingly popular, spatial-temporal text data has increased explosively. Many studies have proposed methods to spatially and temporally analyze an event, indicated by the text data. These studies have aimed a extracting the period and the location in which a specified topic frequently occurs. In this paper, we focus on a system that detects hot topic in a local area and during a particular period. There can be a variation in the words used even though the posts are essentially about the same hot topic. We propose a classification method that mitigates the variation of posted words related to the same topic.

Original languageEnglish
Title of host publicationARCS Workshops, ARCS 2012
Publication statusPublished - Jul 30 2012
Event2012 International Conference on Architecture of Computing Systems, ARCS 2012 - Munchen, Germany
Duration: Feb 28 2012Mar 2 2012

Publication series

NameARCS Workshops, ARCS 2012

Other

Other2012 International Conference on Architecture of Computing Systems, ARCS 2012
CountryGermany
CityMunchen
Period2/28/123/2/12

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Ishikawa, S., Arakawa, Y., Tagashira, S., & Fukuda, A. (2012). Hot topic detection in local areas using Twitter and Wikipedia. In ARCS Workshops, ARCS 2012 [6222198] (ARCS Workshops, ARCS 2012).