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Hot topic detection in local areas using Twitter and Wikipedia

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4 Author(s)
Shota Ishikawa ; Graduate School / Faculty of Information Science and Electrical Engineering, Kyushu University 744 Motooka, Nishi-ku, Fukuoka, Japan ; Yutaka Arakawa ; Shigeaki Tagashira ; Akira Fukuda

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.

Published in:

ARCS Workshops (ARCS), 2012

Date of Conference:

28-29 Feb. 2012