Time-series Visualization of Twitter Trends

Atsuro Konishi, Hiroshi Hosobe

Abstract

Twitter provides a function called “trend” that presents popular words and hashtags. Typically, one trend word or hashtag is related to thousands of tweets. It is difficult to understand such thousands of tweets in a short time by using the standard sort methods and the standard display method provided by Twitter. Most of previous studies analyzed and visualized tweets by using text-based clustering methods. However, these methods suffer from the accuracy of clustering results, because a typical tweet has only poor textual information. This paper presents a Twitter trend analysis system that combines retweet clustering and time-series visualization to allow users to understand flows of topics in a Twitter trend in a short time. This system also provides a list of effective legends and a display of individual tweets with photos in order for users to further understand topics in a trend. To illustrate the effectiveness of this system, this paper presents the results of experiments on the analysis of Twitter trends related to a popular sport event and a popular music program.

Paper Citation

in Harvard Style

Konishi A. and Hosobe H. (2020). Time-series Visualization of Twitter Trends.In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, ISBN 978-989-758-402-2, pages 201-208. DOI: 10.5220/0008964802010208

in Bibtex Style

@conference{ivapp20,
author={Atsuro Konishi and Hiroshi Hosobe},
title={Time-series Visualization of Twitter Trends},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,},
year={2020},
pages={201-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008964802010208},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,
TI - Time-series Visualization of Twitter Trends
SN - 978-989-758-402-2
AU - Konishi A.
AU - Hosobe H.
PY - 2020
SP - 201
EP - 208
DO - 10.5220/0008964802010208