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Authors: Daniel Pereira ; Wladmir Brandão and Mark Song

Affiliation: Programa de Pós-Graduação em Informática, Instituto de Ciências Exatas e Informática, Pontifícia Universidade Católica de Minas Gerais, Brazil

Keyword(s): Topic Evolution, Twitter, Formal Concept Analysis, Social Network Analysis.

Abstract: Social networks became an environment where users express their feeling and share news in real-time. But analyzing the content produced by the users is not simple, considering the number of posts. It is worthy to understand what is being expressed by users to get insights about companies, public figures, and news. To the best of our knowledge, the state-of-the-art lacks proposing studies about how the topics discussed by social network users change over time. In this context, this work measure how topics discussed on Twitter vary over time. We used Formal Concept Analysis to measure how these topics were varying, considering the support and confidence metrics. We tested our solution on two case studies, first using the RepLab 2013 and second creating a database with tweets that discuss vaccines in Brazil. The result confirms that is possible to understand what Twitter users were discussing and how these topics changed over time. Our work benefits companies who want to analyze what us ers are discussing about them. (More)

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Paper citation in several formats:
Pereira, D.; Brandão, W. and Song, M. (2022). Temporal Evolution of Topics on Twitter. In Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-613-2; ISSN 2184-3252, SciTePress, pages 113-119. DOI: 10.5220/0011524500003318

@conference{webist22,
author={Daniel Pereira. and Wladmir Brandão. and Mark Song.},
title={Temporal Evolution of Topics on Twitter},
booktitle={Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST},
year={2022},
pages={113-119},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011524500003318},
isbn={978-989-758-613-2},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST
TI - Temporal Evolution of Topics on Twitter
SN - 978-989-758-613-2
IS - 2184-3252
AU - Pereira, D.
AU - Brandão, W.
AU - Song, M.
PY - 2022
SP - 113
EP - 119
DO - 10.5220/0011524500003318
PB - SciTePress

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