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Twitter Bursts: Analysis of their Occurrences and Classifications

Authors:
Yuhiro Mizunuma
Shuhei Yamamoto
Yutaro Yamaguchi
Atsushi Ikeuchi
Tetsuji Satoh
Satoshi Shimada

Keywords: Twitter; Burst; Clustering

Abstract:
Twitter, a microblogging service launched in October 2006, has become one of the most popular social communication media. Because Twitter's characteristics are immediacy, ease of use, and bi-directionality, its timeline reflects the real world almost instantly. Once a major event happens, the number of tweets increases rapidly. In this article, this phenomenon is defined as a burst. The authors gathered Japanese tweets on a public timeline from Twitter API over a period of fifteen months starting from November, 2011, to February, 2013. We collected over 5 billion posts created by about 11 million users. Results of our analysises show that during the bursts, the total number of tweets showed a higher percentage of retweets, fewer replies, and fewer characters used per post than those during normal status. Cluster analysis revealed five types of bursts. Furthermore, we clarified that the scale of earthquakes in Japan and the distance from the quakes' epicenters to Tokyo significantly affected the occurrence of bursts on Twitter.

Pages: 182 to 187

Copyright: Copyright (c) IARIA, 2014

Publication date: March 23, 2014

Published in: conference

ISSN: 2308-3956

ISBN: 978-1-61208-324-7

Location: Barcelona, Spain

Dates: from March 23, 2014 to March 27, 2014