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Authors: Takako Hashimoto 1 ; Akira Kusaba 2 ; Dave Shepard 3 ; Tetsuji Kuboyama 2 ; Kilho Shin 2 and Takeaki Uno 4

Affiliations: 1 Chiba University of Commerce, Japan ; 2 Gakushuin University, Japan ; 3 University of California, Los Angeles, U.S.A. ; 4 National Institute of Informatics, Japan

Keyword(s): Twitter, Topic Transition Analysis, Micro Clustering, Time Series Analysis.

Abstract: This paper proposes a method for visualizing the progress of a bursty topic on Twitter using a previously-proposed micro-clustering technique, which reveals the cause and the progress of a burst. Micro-clustering can efficiently represent sub-topics of a bursty topic, which allows visualizing transitions between these subtopics over time. This process allows for a Twitter user to see the origin of a bursty topic more easily. To show the method’s effectiveness, we conducted an experiment on a real bursty topic, a controversy over childcare leave in Japan. When we extract sub-topics using micro-clustering, and analyze micro-clusters over time, we can understand the progress of the target topic and discover the micro-clusters that caused the burst.

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Paper citation in several formats:
Hashimoto, T.; Kusaba, A.; Shepard, D.; Kuboyama, T.; Shin, K. and Uno, T. (2020). Twitter Topic Progress Visualization using Micro-clustering. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-397-1; ISSN 2184-4313, SciTePress, pages 585-592. DOI: 10.5220/0009160805850592

@conference{icpram20,
author={Takako Hashimoto. and Akira Kusaba. and Dave Shepard. and Tetsuji Kuboyama. and Kilho Shin. and Takeaki Uno.},
title={Twitter Topic Progress Visualization using Micro-clustering},
booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2020},
pages={585-592},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009160805850592},
isbn={978-989-758-397-1},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Twitter Topic Progress Visualization using Micro-clustering
SN - 978-989-758-397-1
IS - 2184-4313
AU - Hashimoto, T.
AU - Kusaba, A.
AU - Shepard, D.
AU - Kuboyama, T.
AU - Shin, K.
AU - Uno, T.
PY - 2020
SP - 585
EP - 592
DO - 10.5220/0009160805850592
PB - SciTePress