Copa do Mundo da FIFA de 2014: uma análise inicial de sentimentos coletivos no Twitter
Resumo
As comunidades de mídias sociais são geralmente formadas a partir de similaridades entre os usuários. Em redes sociais educacionais, vários fatores propiciam a formação de grupos de usuários, por exemplo, compartilhar o mesmo ambiente acadêmico ou interessados em currículo comum. Para explicar a formação do grupo resultante de uma rede social educacional, aplicamos dois métodos de criação de perfis de grupos baseados na diferenciação. O teste de Wilcoxon e o algoritmo de regras PART foram aplicados a um conjunto de dados disponível da rede social educacional OJE. Os experimentos realizados mostraram que os métodos foram eficazes na criação de perfis, caracterizando 81,81% e 100% dos grupos, respectivamente.
Palavras-chave:
Copa do Mundo, Análise de Sentimentos, Twitter
Referências
Blog, T. (2014). Insights into the #worldcup conversation on twitter. Access in: 2014/09/10.
Firmino Alves, A. L., Baptista, C. d. S., Firmino, A. A., Oliveira, M. G. a. d., and Paiva, A. C. d. (2014). A comparison of svm versus naive-bayes techniques for sentiment analysis in tweets: A case study with the 2013 fifa confederations cup. In Proceedings of the 20th Brazilian Symposium on Multimedia and the Web, WebMedia ’14, pages 123–130, New York, NY, USA. ACM.
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Hassan, A., Abbasi, A., and Zeng, D. (2013). Twitter sentiment analysis: A bootstrap ensemble framework. In Social Computing (SocialCom), 2013 International Conference on, pages 357–364.
Kwak, H., Lee, C., Park, H., and Moon, S. (2010). What is twitter, a social network or a news media? In Proceedings of the 19th International Conference on World Wide Web, WWW ’10, pages 591–600, New York, NY, USA. ACM.
Liu, B. and Zhang, L. (2012). A survey of opinion mining and sentiment analysis. In Aggarwal, C. C. and Zhai, C., editors, Mining Text Data, pages 415–463. Springer US.
Nguyen, V. D., Varghese, B., and Barker, A. (2013). The royal birth of 2013: Analysing and visualising public sentiment in the uk using twitter. In Big Data, 2013 IEEE International Conference on, pages 46–54.
Pak, A. and Paroubek, P. (2010). Twitter as a corpus for sentiment analysis and opinion mining. In Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC’10), Valletta, Malta. European Language Resources Association (ELRA).
Pang, B. and Lee, L. (2008). Opinion mining and sentiment analysis. Found. Trends Inf. Retr., 2(1-2):1–135.
Sakaki, T., Okazaki, M., and Matsuo, Y. (2010). Earthquake shakes twitter users: Realtime event detection by social sensors. In Proceedings of the 19th International Conference on World Wide Web, WWW ’10, pages 851–860, New York, NY, USA. ACM.
Thelwall, M. and Cybermetrics. Heart and Soul: Sentiment Strength Detection in the Social Web with SentiStrength 1. 5.
Twitter (2014). About twitter, inc. — about. Access in: 2014/08/15.
Firmino Alves, A. L., Baptista, C. d. S., Firmino, A. A., Oliveira, M. G. a. d., and Paiva, A. C. d. (2014). A comparison of svm versus naive-bayes techniques for sentiment analysis in tweets: A case study with the 2013 fifa confederations cup. In Proceedings of the 20th Brazilian Symposium on Multimedia and the Web, WebMedia ’14, pages 123–130, New York, NY, USA. ACM.
Gonçalves, P., Aráujo, M., Benevenuto, F., and Cha, M. (2013). Comparing and combining sentiment analysis methods. In Proceedings of the First ACM Conference on Online Social Networks, COSN ’13, pages 27–38, New York, NY, USA. ACM.
Hassan, A., Abbasi, A., and Zeng, D. (2013). Twitter sentiment analysis: A bootstrap ensemble framework. In Social Computing (SocialCom), 2013 International Conference on, pages 357–364.
Kwak, H., Lee, C., Park, H., and Moon, S. (2010). What is twitter, a social network or a news media? In Proceedings of the 19th International Conference on World Wide Web, WWW ’10, pages 591–600, New York, NY, USA. ACM.
Liu, B. and Zhang, L. (2012). A survey of opinion mining and sentiment analysis. In Aggarwal, C. C. and Zhai, C., editors, Mining Text Data, pages 415–463. Springer US.
Nguyen, V. D., Varghese, B., and Barker, A. (2013). The royal birth of 2013: Analysing and visualising public sentiment in the uk using twitter. In Big Data, 2013 IEEE International Conference on, pages 46–54.
Pak, A. and Paroubek, P. (2010). Twitter as a corpus for sentiment analysis and opinion mining. In Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC’10), Valletta, Malta. European Language Resources Association (ELRA).
Pang, B. and Lee, L. (2008). Opinion mining and sentiment analysis. Found. Trends Inf. Retr., 2(1-2):1–135.
Sakaki, T., Okazaki, M., and Matsuo, Y. (2010). Earthquake shakes twitter users: Realtime event detection by social sensors. In Proceedings of the 19th International Conference on World Wide Web, WWW ’10, pages 851–860, New York, NY, USA. ACM.
Thelwall, M. and Cybermetrics. Heart and Soul: Sentiment Strength Detection in the Social Web with SentiStrength 1. 5.
Twitter (2014). About twitter, inc. — about. Access in: 2014/08/15.
Publicado
01/08/2015
Como Citar
BARROS FILHO, Rubens; MAGALHÃES, Jonathas; SILVA, Marlos; COSTA, Evandro; LUNA, Henrique.
Copa do Mundo da FIFA de 2014: uma análise inicial de sentimentos coletivos no Twitter. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 4. , 2015, Recife.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2015
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p. .
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2015.6798.
