TRENDSPOTTER DETECTION SYSTEM FOR TWITTER

Wataru Shirakihara, Tetsuya Oishi, Ryuzo Hasegawa, Hiroshi Hujita, Miyuki Koshimura

Abstract

It is too difficult for us to find out trends with search engines. Twitter, a popular microblogging tool, has seen a lot of growth since it launched in October, 2006. Information about the trends is posted by many twitterers. If we find out trendspotters from twitterers, and follow them, we can get it more easily. Our trendspotter detection system uses the burst detection algorithm, and we verified its effectiveness for Twitter’s posts. We succeeded in detecting the 24 trendspotters by 5277 users.

References

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Paper Citation


in Harvard Style

Shirakihara W., Oishi T., Hasegawa R., Hujita H. and Koshimura M. (2011). TRENDSPOTTER DETECTION SYSTEM FOR TWITTER . In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-40-9, pages 625-628. DOI: 10.5220/0003183806250628


in Bibtex Style

@conference{icaart11,
author={Wataru Shirakihara and Tetsuya Oishi and Ryuzo Hasegawa and Hiroshi Hujita and Miyuki Koshimura},
title={TRENDSPOTTER DETECTION SYSTEM FOR TWITTER},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2011},
pages={625-628},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003183806250628},
isbn={978-989-8425-40-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - TRENDSPOTTER DETECTION SYSTEM FOR TWITTER
SN - 978-989-8425-40-9
AU - Shirakihara W.
AU - Oishi T.
AU - Hasegawa R.
AU - Hujita H.
AU - Koshimura M.
PY - 2011
SP - 625
EP - 628
DO - 10.5220/0003183806250628