Caracterização da Propagação de Rumores no Twitter utilizando Redes Textuais Temporais
Resumo
Plataformas de mídias sociais são o principal meio de difusão de informação e notícias, sendo valiosas em muitas aplicações. Ao mesmo tempo, são plataformas que potencializam a difusão de rumores e notícias falsas. Três elementos fundamentais para entender a informação trocada entre pessoas em redes sociais são os indivíduos ou atores, a informação que eles trocam e o tempo quando tais informações são trocadas. Neste artigo é apresentada uma análise da propagação de rumores utilizando estruturas de redes textuais temporais. Os resultados indicam que tais estruturas são ideais para análise do problema de propagação de rumores no Twitter.
Palavras-chave:
deteção de rumores, redes textuais temporais, análise de redes sociais
Referências
Kochkina, E., Liakata, M., and Zubiaga, A. (2018). All-in-one: Multi-task learning for rumour verification. In Proceedings of the 27th International Conference on Compu- tational Linguistics, pages 3402–3413. Association for Computational Linguistics.
Kotteti, C. M. M., Dong, X., and Qian, L. (2020). Ensemble deep learning on time-series representation of tweets for rumor detection in social media. CoRR, abs/2004.12500.
Pierri, F. and Ceri, S. (2019). False news on social media: A data-driven survey. SIGMOD Rec., 48(2):18–27.
Vega, D. and Magnani, M. (2018). Foundations of temporal text networks. Applied Network Science, 3(25).
Vega, D. and Magnani, M. (2019). Metrics for Temporal Text Networks, pages 147–160. Springer International Publishing, Cham.
Vosoughi, S., Roy, D., and Aral, S. (2018). The spread of true and false news online. Science, 6380(359).
Wu, L., Morstatter, F., Carley, K. M., and Liu, H. (2019). Misinformation in social me- dia: Definition, manipulation, and detection. ACM SIGKDD Explorations Newsletter, 21(2):80–90
Yang, X., Lyu, Y., Tian, T., Liu, Y., Liu, Y., and Zhang, X. (2020). Rumor detection on social media with graph structured adversarial learning. In Bessiere, C., editor, Pro- ceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI-20, pages 1417–1423. International Joint Conferences on Artificial Intelligence Organization.
Zhao, Z., Resnick, P., and Mei, Q. (2015). Enquiring minds: Early detection of rumors in social media from enquiry posts. In Proceedings of the 24th International Con- ference on World Wide Web, WWW ’15, page 1395–1405. International World Wide Web Conferences Steering Committee.
Zubiaga, A., Aker, A., Bontcheva, K., Liakata, M., and Procter, R. (2018). Detection and resolution of rumours in social media: A survey. ACM Comput. Surv., 51(2).
Zubiaga, A., Liakata, M., and Procter, R. (2016). Learning reporting dynamics during breaking news for rumour detection in social media. CoRR, abs/1610.07363.
Kotteti, C. M. M., Dong, X., and Qian, L. (2020). Ensemble deep learning on time-series representation of tweets for rumor detection in social media. CoRR, abs/2004.12500.
Pierri, F. and Ceri, S. (2019). False news on social media: A data-driven survey. SIGMOD Rec., 48(2):18–27.
Vega, D. and Magnani, M. (2018). Foundations of temporal text networks. Applied Network Science, 3(25).
Vega, D. and Magnani, M. (2019). Metrics for Temporal Text Networks, pages 147–160. Springer International Publishing, Cham.
Vosoughi, S., Roy, D., and Aral, S. (2018). The spread of true and false news online. Science, 6380(359).
Wu, L., Morstatter, F., Carley, K. M., and Liu, H. (2019). Misinformation in social me- dia: Definition, manipulation, and detection. ACM SIGKDD Explorations Newsletter, 21(2):80–90
Yang, X., Lyu, Y., Tian, T., Liu, Y., Liu, Y., and Zhang, X. (2020). Rumor detection on social media with graph structured adversarial learning. In Bessiere, C., editor, Pro- ceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI-20, pages 1417–1423. International Joint Conferences on Artificial Intelligence Organization.
Zhao, Z., Resnick, P., and Mei, Q. (2015). Enquiring minds: Early detection of rumors in social media from enquiry posts. In Proceedings of the 24th International Con- ference on World Wide Web, WWW ’15, page 1395–1405. International World Wide Web Conferences Steering Committee.
Zubiaga, A., Aker, A., Bontcheva, K., Liakata, M., and Procter, R. (2018). Detection and resolution of rumours in social media: A survey. ACM Comput. Surv., 51(2).
Zubiaga, A., Liakata, M., and Procter, R. (2016). Learning reporting dynamics during breaking news for rumour detection in social media. CoRR, abs/1610.07363.
Publicado
18/07/2021
Como Citar
PEREIRA, Fabíola S. F..
Caracterização da Propagação de Rumores no Twitter utilizando Redes Textuais Temporais. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 10. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 25-31.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2021.16122.
