Twitter Topic Progress Visualization using Micro-clustering

Takako Hashimoto, Akira Kusaba, Dave Shepard, Tetsuji Kuboyama, Kilho Shin, Takeaki Uno

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 Harvard Style

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 - Volume 1: ICPRAM, ISBN 978-989-758-397-1, pages 585-592. DOI: 10.5220/0009160805850592


in Bibtex Style

@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 - Volume 1: ICPRAM,},
year={2020},
pages={585-592},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009160805850592},
isbn={978-989-758-397-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Twitter Topic Progress Visualization using Micro-clustering
SN - 978-989-758-397-1
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