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.
DownloadPaper 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