Utilizando Análise de Sentimentos para Definição da Homofilia Política dos Usuários do Twitter durante a Eleição Presidencial Americana de 2016
Resumo
Este trabalho propõe uma análise da homofilia política entre usuários do Twitter durante a eleição presidencial americana de 2016. Os tweets, perfis de usuários e suas redes de contatos foram coletados para este estudo ao longo de 122 dias (01/08/2016 até 30/11/2016). Considerando a base de dados coletada, o sentimento em relação aos candidatos Donald Trump e Hillary Clinton foi utilizado para a análise da homofilia. Os resultados mostraram que existe maior homofilia entre usuários que compartilham sentimento negativo em relação a ambos candidatos, sendo mais evidente no caso do candidato Donald Trump. Os resultados também mostraram que existe maior heterofilia entre usuários que não manifestaram sentimento em relação aos dois candidatos.
Referências
Colleoni, E., Rozza, A., and Arvidsson, A. (2014). Echo chamber or public sphere? predicting political orientation and measuring political homophily in twitter using big data. Journal of Communication, 64(2):317–332.
Currarini, S., Jackson, M. O., and Pin, P. (2009). An economic model of friendship: Homophily, minorities, and segregation. Econometrica, 77(4):1003–1045.
DeMasi, O., Mason, D., and Ma, J. (2016). Understanding communities via hashtag engagement: A clustering based approach. In Tenth International AAAI Conference on Web and Social Media.
Easley, D. and Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press.
Ferrara, E. and Yang, Z. (2015). Measuring emotional contagion in social media. PLOS ONE, 10(11):1–14.
Giachanou, A. and Crestani, F. (2016). Like it or not: A survey of twitter sentiment analysis methods. ACM Comput. Surv., 49(2):28:1–28:41.
Halberstam, Y. and Knight, B. (2016). Homophily, group size, and the diffusion of political information in social networks: Evidence from twitter. Journal of Public Economics, 143:73–88.
Klein, D., Manning, C. D., et al. (2003). Fast exact inference with a factored model for natural language parsing. Advances in neural information processing systems, pages 3–10.
McPherson, M., Smith-Lovin, L., and Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual review of sociology, pages 415–444.
Ribeiro, E. M. B. and Bastos, A. V. B. (2014). A homofilia por cotas em cursos de alta e baixa concorrência na universidade federal da bahia. In XXIV Congresso da Sociedade Brasileira de Computação. III Brazilian Workshop on Social Network Analysis and Mining.
Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., and Kappas, A. (2010). Sentiment in short strength detection informal text. J. Am. Soc. Inf. Sci. Technol., 61(12):2544–2558.
Wang, H., Can, D., Kazemzadeh, A., Bar, F., and Narayanan, S. (2012). A system for real-time twitter sentiment analysis of 2012 u.s. presidential election cycle. In Proceedings of the ACL 2012 System Demonstrations, ACL ’12, pages 115–120, Stroudsburg, PA, USA. Association for Computational Linguistics.
Yuan, G., Murukannaiah, P. K., Zhang, Z., and Singh, M. P. (2014). Exploiting sentiment homophily for link prediction. In Proceedings of the 8th ACM Conference on Recommender Systems, RecSys ’14, pages 17–24, New York, NY, USA. ACM.
Currarini, S., Jackson, M. O., and Pin, P. (2009). An economic model of friendship: Homophily, minorities, and segregation. Econometrica, 77(4):1003–1045.
DeMasi, O., Mason, D., and Ma, J. (2016). Understanding communities via hashtag engagement: A clustering based approach. In Tenth International AAAI Conference on Web and Social Media.
Easley, D. and Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press.
Ferrara, E. and Yang, Z. (2015). Measuring emotional contagion in social media. PLOS ONE, 10(11):1–14.
Giachanou, A. and Crestani, F. (2016). Like it or not: A survey of twitter sentiment analysis methods. ACM Comput. Surv., 49(2):28:1–28:41.
Halberstam, Y. and Knight, B. (2016). Homophily, group size, and the diffusion of political information in social networks: Evidence from twitter. Journal of Public Economics, 143:73–88.
Klein, D., Manning, C. D., et al. (2003). Fast exact inference with a factored model for natural language parsing. Advances in neural information processing systems, pages 3–10.
McPherson, M., Smith-Lovin, L., and Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual review of sociology, pages 415–444.
Ribeiro, E. M. B. and Bastos, A. V. B. (2014). A homofilia por cotas em cursos de alta e baixa concorrência na universidade federal da bahia. In XXIV Congresso da Sociedade Brasileira de Computação. III Brazilian Workshop on Social Network Analysis and Mining.
Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., and Kappas, A. (2010). Sentiment in short strength detection informal text. J. Am. Soc. Inf. Sci. Technol., 61(12):2544–2558.
Wang, H., Can, D., Kazemzadeh, A., Bar, F., and Narayanan, S. (2012). A system for real-time twitter sentiment analysis of 2012 u.s. presidential election cycle. In Proceedings of the ACL 2012 System Demonstrations, ACL ’12, pages 115–120, Stroudsburg, PA, USA. Association for Computational Linguistics.
Yuan, G., Murukannaiah, P. K., Zhang, Z., and Singh, M. P. (2014). Exploiting sentiment homophily for link prediction. In Proceedings of the 8th ACM Conference on Recommender Systems, RecSys ’14, pages 17–24, New York, NY, USA. ACM.
Publicado
02/07/2017
Como Citar
CAETANO, Josemar Alves; LIMA, Hélder Seixas; DOS SANTOS, Mateus Freira; MARQUES-NETO, Humberto Torres.
Utilizando Análise de Sentimentos para Definição da Homofilia Política dos Usuários do Twitter durante a Eleição Presidencial Americana de 2016. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 6. , 2017, São Paulo.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2017
.
p. 480-491.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2017.3246.
