Notícias relacionadas a pessoas com deficiência: uma análise do conteúdo gerado pelos usuários em postagens de mídias sociais
Resumo
As mídias sociais desempenham um papel essencial para as pessoas com deficiência e seus familiares por proporcionarem um canal de denúncia e induzirem a construção de redes de apoio. No entanto, discursos de ódio também são encontrados nessas mídias. Nesse sentido, uma análise das postagens de mídia social sobre notícias relacionadas à deficiência no Brasil é apresentada neste artigo. Os comentários da mídia foram coletados e analisados usando modelagem de tópicos e análise de sentimentos. Além disso, as postagens foram classificadas de acordo com o seu conteúdo. Os resultados mostram que há uma busca sobre o assunto, principalmente em relação a reclamações ou em busca de apoio mútuo. Os achados da pesquisa podem guiar a formação de uma rede de apoio às pessoas com deficiência e suas famílias.
Palavras-chave:
Análise de Mídias Sociais, Notícias, Deficiência, Pessoas com Deficiência, Conteúdo Gerado pelo Usuário
Referências
Almeida, G. R. d., Cirqueira, D. R., and Lobato, F. M. (2017). Improving Social CRM through eletronic word-of-mouth: a case study of ReclameAqui. XIV Workshop de Trabalhos de Iniciaçao Cientıfica (WTIC 2017).
Brookes, G. and McEnery, T. (2019). The utility of topic modelling for discourse studies: A critical evaluation. Discourse Studies, 21(1):3–21.
Buchholz, M., Ferm, U., and Holmgren, K. (2018). Support persons’ views on remote communication and social media for people with communicative and cognitive disabilities. Disability and Rehabilitation, 0(0):1–9.
Caldas, L. V. A., Jacob, A. F. L., Silva, S. S. C., Pontes, F. A. R., and Lobato, F. M. F. (2018). Development of a social network for research support and individual wellbeing improvement. In Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pages 383–386.
Chen, Z., Mukherjee, A., Liu, B., Hsu, M., Castellanos, M., and Ghosh, R. (2013). Leveraging multi-domain prior knowledge in topic models. In Twenty-Third International Joint Conference on Artificial Intelligence.
Cirqueira, D., Fontes Pinheiro, M., Jacob, A., Lobato, F., and Santana, A. (2018). A Literature Review in Preprocessing for Sentiment Analysis for Brazilian Portuguese Social Media. In Proceedings of the 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), pages 746–749. IEEE.
Cirqueira, D., Jacob, A., Lobato, F., de Santana, A. L., and Pinheiro, M. (2017). Performance Evaluation of Sentiment Analysis Methods for Brazilian Portuguese. In Abramowicz, W., Alt, R., and Franczyk, B., editors, Business Information Systems Workshops: BIS 2016 International Workshops, Leipzig, Germany, July 6-8, 2016, Revised Papers, pages 245–251. Springer International Publishing, Cham.
Correa, I. T., Abdala, D. D., Miani, R. S., and Faria, E. R. (2018). Sentiment Analysis of Twitter Posts About the 2017 Academy Awards. In Anais do XV Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2018), pages 320–331. Sociedade Brasileira de Computação - SBC.
Djuric, N., Zhou, J., Morris, R., Grbovic, M., Radosavljevic, V., and Bhamidipati, N. (2015). Hate Speech Detection with Comment Embeddings. In Proceedings of the 24th International Conference on World Wide Web - WWW ’15 Companion, pages 29– 30, New York, New York, USA. ACM Press.
ElSherief, M., Kulkarni, V., Nguyen, D., Wang, W. Y., and Belding, E. (2018). Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media. In Proceedings of the 12th International AAAI Conference on Web and Social Media, pages 42–51.
Figueira, Á. and Guimarães, N. (2017). Detecting Journalistic Relevance on Social Media. Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 - ASONAM ’17, pages 1136–1139.
Kilburn, J. E. and Shapiro, C. J. (2018). The structure and function of social networks of mothers of young children with disabilities. Topics in Early Childhood Special Education, page 0271121418767306.
Lima, J. M. C. and Maia, J. E. B. (2018). A Topical Word Embeddings for Text Classification. In Anais do XV Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2018), pages 25–35. Sociedade Brasileira de Computação - SBC.
Lobato, F., Pinheiro, M., Jacob, A., Reinhold, O., and Santana, Á. (2017). Social CRM: Biggest challenges to make it work in the real world. In Abramowicz, W., Alt, R., and Franczyk, B., editors, Business Information Systems Workshops: BIS 2016 International Workshops, Leipzig, Germany, July 6-8, 2016, Revised Papers, pages 221–232. Springer International Publishing, Cham.
Lobato, F. M. F., da Silva, M., Coelho, K., da Costa Silva, S., and Pontes, F. (2018). Vamos falar sobre deficiência? Uma análise dos Tweets sobre este tema no Brasil. Proceedings of the 7th Brazilian Workshop on Social Network Analysis and Mining, pages 274–279.
Magalhães, G. G. M. S. d., Lima, F., Santos, E. F., Junior, P., and Rosa, L. (2017). Seleção de Técnicas de Mineração de Dados para Segmentação de Mercado. In Proceedings of the 6th Brazilian Workshop on Social Network Analysis and Mining, pages 658–669.
Mondal, M., Silva, L. A., and Benevenuto, F. (2017). A Measurement Study of Hate Speech in Social Media. In Proceedings of the 28th ACM Conference on Hypertext and Social Media - HT ’17, pages 85–94, New York, New York, USA. ACM Press.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12:2825–2830.
Ramos, P., Reis, J., and Benevenuto, F. (2016). Uma Análise da Polaridade Expressa nas Manchetes de Notı́cias Brasileiras. In Proceedings of the 5th Brazilian Workshop on Social Network Analysis and Mining, pages 187–198.
Silva, W., Santana, Á., Lobato, F., and Pinheiro, M. (2017). A Methodology for Comunity Detection in Twitter. In Proceedings of the International Conference on Web Intelligence, pages 1006–1009.
Simões, A., Athias, L., and Botelho, L. (2018). Panorama Nacional e Internacional da Produção de Indicadores Sociais. Instituto Brasileiro de Geografia e Estatı́stica (IBGE), Rio de Janeiro, 6th edition.
Teixeira, M. A. M., Lobato, F. M. F., Chagas, B. N. R., and Jacob Junior, A. F. L. (2018). A System of Acquisition and Analysis of Data for Extraction of Knowledge of the Ebit Platform. In Proceedings of the 15th International Conference on Information Systems & Technology Management, pages 4195–4206.
Williams, T. and Betak, J. (2018). A Comparison of LSA and LDA for the Analysis of Railroad Accident Text. In Proceedings of the 9th International Conference on Ambient Systems, Networks and Technologies (ANT 2018), pages 98–102.
Xavier, C. C. (2018). Polarity Classification of Traffic Related Tweets. In Anais do XV Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2018), pages 206–215. Sociedade Brasileira de Computação - SBC.
Yesbeck, J. (2018). How are Alexa’s traffic rankings determined?
Brookes, G. and McEnery, T. (2019). The utility of topic modelling for discourse studies: A critical evaluation. Discourse Studies, 21(1):3–21.
Buchholz, M., Ferm, U., and Holmgren, K. (2018). Support persons’ views on remote communication and social media for people with communicative and cognitive disabilities. Disability and Rehabilitation, 0(0):1–9.
Caldas, L. V. A., Jacob, A. F. L., Silva, S. S. C., Pontes, F. A. R., and Lobato, F. M. F. (2018). Development of a social network for research support and individual wellbeing improvement. In Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pages 383–386.
Chen, Z., Mukherjee, A., Liu, B., Hsu, M., Castellanos, M., and Ghosh, R. (2013). Leveraging multi-domain prior knowledge in topic models. In Twenty-Third International Joint Conference on Artificial Intelligence.
Cirqueira, D., Fontes Pinheiro, M., Jacob, A., Lobato, F., and Santana, A. (2018). A Literature Review in Preprocessing for Sentiment Analysis for Brazilian Portuguese Social Media. In Proceedings of the 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), pages 746–749. IEEE.
Cirqueira, D., Jacob, A., Lobato, F., de Santana, A. L., and Pinheiro, M. (2017). Performance Evaluation of Sentiment Analysis Methods for Brazilian Portuguese. In Abramowicz, W., Alt, R., and Franczyk, B., editors, Business Information Systems Workshops: BIS 2016 International Workshops, Leipzig, Germany, July 6-8, 2016, Revised Papers, pages 245–251. Springer International Publishing, Cham.
Correa, I. T., Abdala, D. D., Miani, R. S., and Faria, E. R. (2018). Sentiment Analysis of Twitter Posts About the 2017 Academy Awards. In Anais do XV Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2018), pages 320–331. Sociedade Brasileira de Computação - SBC.
Djuric, N., Zhou, J., Morris, R., Grbovic, M., Radosavljevic, V., and Bhamidipati, N. (2015). Hate Speech Detection with Comment Embeddings. In Proceedings of the 24th International Conference on World Wide Web - WWW ’15 Companion, pages 29– 30, New York, New York, USA. ACM Press.
ElSherief, M., Kulkarni, V., Nguyen, D., Wang, W. Y., and Belding, E. (2018). Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media. In Proceedings of the 12th International AAAI Conference on Web and Social Media, pages 42–51.
Figueira, Á. and Guimarães, N. (2017). Detecting Journalistic Relevance on Social Media. Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 - ASONAM ’17, pages 1136–1139.
Kilburn, J. E. and Shapiro, C. J. (2018). The structure and function of social networks of mothers of young children with disabilities. Topics in Early Childhood Special Education, page 0271121418767306.
Lima, J. M. C. and Maia, J. E. B. (2018). A Topical Word Embeddings for Text Classification. In Anais do XV Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2018), pages 25–35. Sociedade Brasileira de Computação - SBC.
Lobato, F., Pinheiro, M., Jacob, A., Reinhold, O., and Santana, Á. (2017). Social CRM: Biggest challenges to make it work in the real world. In Abramowicz, W., Alt, R., and Franczyk, B., editors, Business Information Systems Workshops: BIS 2016 International Workshops, Leipzig, Germany, July 6-8, 2016, Revised Papers, pages 221–232. Springer International Publishing, Cham.
Lobato, F. M. F., da Silva, M., Coelho, K., da Costa Silva, S., and Pontes, F. (2018). Vamos falar sobre deficiência? Uma análise dos Tweets sobre este tema no Brasil. Proceedings of the 7th Brazilian Workshop on Social Network Analysis and Mining, pages 274–279.
Magalhães, G. G. M. S. d., Lima, F., Santos, E. F., Junior, P., and Rosa, L. (2017). Seleção de Técnicas de Mineração de Dados para Segmentação de Mercado. In Proceedings of the 6th Brazilian Workshop on Social Network Analysis and Mining, pages 658–669.
Mondal, M., Silva, L. A., and Benevenuto, F. (2017). A Measurement Study of Hate Speech in Social Media. In Proceedings of the 28th ACM Conference on Hypertext and Social Media - HT ’17, pages 85–94, New York, New York, USA. ACM Press.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12:2825–2830.
Ramos, P., Reis, J., and Benevenuto, F. (2016). Uma Análise da Polaridade Expressa nas Manchetes de Notı́cias Brasileiras. In Proceedings of the 5th Brazilian Workshop on Social Network Analysis and Mining, pages 187–198.
Silva, W., Santana, Á., Lobato, F., and Pinheiro, M. (2017). A Methodology for Comunity Detection in Twitter. In Proceedings of the International Conference on Web Intelligence, pages 1006–1009.
Simões, A., Athias, L., and Botelho, L. (2018). Panorama Nacional e Internacional da Produção de Indicadores Sociais. Instituto Brasileiro de Geografia e Estatı́stica (IBGE), Rio de Janeiro, 6th edition.
Teixeira, M. A. M., Lobato, F. M. F., Chagas, B. N. R., and Jacob Junior, A. F. L. (2018). A System of Acquisition and Analysis of Data for Extraction of Knowledge of the Ebit Platform. In Proceedings of the 15th International Conference on Information Systems & Technology Management, pages 4195–4206.
Williams, T. and Betak, J. (2018). A Comparison of LSA and LDA for the Analysis of Railroad Accident Text. In Proceedings of the 9th International Conference on Ambient Systems, Networks and Technologies (ANT 2018), pages 98–102.
Xavier, C. C. (2018). Polarity Classification of Traffic Related Tweets. In Anais do XV Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2018), pages 206–215. Sociedade Brasileira de Computação - SBC.
Yesbeck, J. (2018). How are Alexa’s traffic rankings determined?
Publicado
15/10/2019
Como Citar
RODRIGUES, Lucas; B. JUNIOR, Ademir; LOBATO, Fabio.
Notícias relacionadas a pessoas com deficiência: uma análise do conteúdo gerado pelos usuários em postagens de mídias sociais. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 16. , 2019, Salvador.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 811-822.
ISSN 2763-9061.
DOI: https://doi.org/10.5753/eniac.2019.9336.
