BRIMO: a Sentiment Analysis Tool
Abstract
Twitter is one of the fastest growing social networks in recent years, being one of the main platforms for people to share their opinions through short posts called tweets. Every trending topic generates rich discussions, and an analysis of people's sentiments about a topic provides a more comprehensive understanding of the subject. However, to our knowledge, there are no tools that make this type of analysis accessible to the general public. Thus, we propose BRIMO, a free web tool with simple and intuitive interface, which allows the analysis of sentiments quickly and objectively, through graphical representations of data. We evaluated BRIMO's usability and usefulness with target users. The results indicate that the tool has great usability according to the criteria used, in addition to being useful for several purposes, in the perception of participants.
Keywords:
Sentiment Analysis, Twitter, Web tool
References
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Brooke, J. (1995). Sus: A quick and dirty usability scale. Usability Eval. Ind., 189.
Burbach, L., Halbach, P., Ziefle, M., and Calero Valdez, A. (2020). Opinion formation on the internet: The influence of personality, network structure, and content on sharing messages online. Frontiers in Artificial Intelligence, 3.
Cardozo, L. and Freitas, L. (2021). Análise de sentimentos: Avaliando o desempenho de pré-processamento e de algoritmos de aprendizagem de máquina sobre o dataset tweetsentbr. In Anais do X Brazilian Workshop on Social Network Analysis and Mining, pages 169–174, Porto Alegre, RS, Brasil. SBC.
Euzebio, C., Agy, S., Boldorini Jr, C., Porto, L., Alcarás, J. R., Martinez, A., and Ruiz, E. (2020). Statistical analysis of small twitter data collection to identify dengue outbreaks. In Anais do VIII Symposium on Knowledge Discovery, Mining and Learning, pages 17–24. SBC.
Fang, X. Zhan, J. (2015). Sentiment analysis using product review data. Journal of Big Data, 2(5):1–14.
França de Souza, K., Ramos Pereira, M. H., and Hasan Dalip, D. (2017). Unilex: Método léxico para análise de sentimentos textuais sobre conteúdo de tweets em português brasileiro. Abakós, 5(2):79–96.
Grier, R. A., Bangor, A., Kortum, P., and Peres, S. C. (2013). The system usability scale: Beyond standard usability testing. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 57(1):187–191.
Lauand, B. P. and Oliveira, J. (2014). Inferindo as condições de trânsito através da análise de sentimentos no twitter. iSys - Brazilian Journal of Information Systems, 10(1):56–74.
Lokesh, K. Parul, K. B. (2013). Text mining: Concepts, process and applications. Journal of Global Research in Computer Science, 4(3):36–39.
Marcec, R. and Likic, R. (2021). Using twitter for sentiment analysis towards astrazeneca/oxford, pfizer/biontech and moderna covid-19 vaccines. Postgraduate medical journal, pages postgradmedj–2021–140685.
Misuraca, M., Forciniti, A., Scepi, G., and Spano, M. (2020). Sentiment Analysis for Education with R: packages, methods and practical applications. arXiv preprint arXiv:2005.12840.
Murakami, H., Ejima, N., and Kumagai, N. (2020). Self-understanding Support Tool Using Twitter Sentiment Analysis, pages 327–332. Springer, New York, NY.
Nielsen, J. (2000). Why you only need to test with 5 users. "Disponível em: https://www.nngroup.com/articles/why-you-only-need-to-test-with-5-users/". Acesso em: 19 mai. 2022.
Ribeiro, A. P. and da Silva, N. F. F. (2018). Um estudo comparativo sobre métodos de análise de sentimentos em tweets. Revista de Sistemas de Informação da FSMA, (22):35–48.
Silva, H., Andrade, E., Araújo, D., and Dantas, J. (2021). Sentiment analysis of tweets related to sus before and during covid-19 pandemic. IEEE Latin America Transactions, 20(1):6–13.
Statista (2022). Most popular social networks worldwide as of january 2022, ranked by number of monthly active users. ”Disponível em: [link]. Acesso em: 19 mai. 2022.
Wunderlich, F. and Memmert, D. (2020). Innovative approaches in sports science—lexicon-based sentiment analysis as a tool to analyze sports-related twitter communication. Applied sciences, 10(2):431.
Published
2022-07-31
How to Cite
ALVES, Otávio; FALCÃO, Taciana Pontual; VALENÇA, George; ANDRADE, Ermeson.
BRIMO: a Sentiment Analysis Tool. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 11. , 2022, Niterói.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 97-108.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2022.222842.
