Análise exploratória de tweets do Governo de Santa Catarina utilizando Modelagem de Tópicos
Abstract
Topic modeling approaches have been widely used to discover latent topics from document collections. Twitter is one of the most used microblogs to spread news to people. Based on tweets extracted from the Santa Catarina official account from 2019 to 2021, we propose a set of experiments to discover the main subjects discussed in that period. As a result, we could identify the most important subjects that were discussed and presented to the Santa Catarina citizens.
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Chehal, D., Gupta, P., and Gulati, P. (2021). Implementation and comparison of topic modeling techniques based on user reviews in e-commerce recommendations. Journal of Ambient Intelligence and Humanized Computing, 12(5):5055–5070.
Duarte, D. and Stahl, N. (2019). Machine learning: a concise overview. In Said, A. and Torra, V., editors, Data Science in Practice, pages 27–58. Springer.
Fukuyama, S. and Wakabayashi, K. (2018). Extracting time series variation of topic popularity in microblogs. In Proceedings of iiWAS, pages 365–369, New York, New York, USA. ACM.
Hidayatullah, A. F., Pembrani, E. C., Kurniawan, W., Akbar, G., and Pranata, R. (2018). Twitter topic modeling on football news. In 2018 3rd ICCCS, pages 467–471. IEEE.
Pereira, M. (2019). Análise exploratória de tweets utilizando modelagem de tópicos para textos curtos: caso olimpíadas rio 2016. [link]. Monografia, UFFS, Chapeco, Brasil.
Roder, M., Both, A., and Hinneburg, A. (2015). Exploring the space of topic coherence measures. In Proceedings of the Eighth WSDM, pages 399–408, USA. ACM.
Steyvers, M. and Griffiths, T. (2007). Probabilistic topic models. In Landauer, T. K., McNamara, D. S., Dennis, S., and Kintsch, W., editors, Handbook of latent semantic analysis, chapter 21, pages 424–440. Laurence Erlbaum Associates.
Yan, X., Guo, J., Lan, Y., and Cheng, X. (2013). A biterm topic model for short texts. In Proceedings of the 22nd WWW. ACM.
Published
2022-06-27
How to Cite
ROCHA, Leonardo H.; DUARTE, Denio; SCHREINER, Geomar A.; DAL BIANCO, Guilherme.
Análise exploratória de tweets do Governo de Santa Catarina utilizando Modelagem de Tópicos. In: REGIONAL DATABASE SCHOOL (ERBD), 17. , 2022, Lages/SC.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 71-80.
ISSN 2595-413X.
DOI: https://doi.org/10.5753/erbd.2022.223538.
