FacTweet: Profiling Fake News Twitter Accounts
[EN] We present an approach to detect fake news in Twitter at the account level using a neural recurrent model and a variety of different semantic and stylistic features. Our method extracts a set of features from the timelines of news Twitter accounts by reading their posts as chunks, rather than dealing with each tweet independently. We show the experimental benefits of modeling latent stylistic signatures of mixed fake and real news with a sequential model over a wide range of strong baselines ; The work of Paolo Rosso was partially funded by the Spanish MICINN under the research project MISMIS-FAKEnHATE on Misinformation and Miscommunication in social media: FAKE news and HATE speech (PGC2018-096212-B-C31) ; Ghanem, BHH.; Ponzetto, SP.; Rosso, P. (2020). FacTweet: Profiling Fake News Twitter Accounts. Springer. 35-45. https://doi.org/10.1007/978-3-030-59430-5_3 ; S ; 35 ; 45 ; Aker, A., Kevin, V., Bontcheva, K.: Credibility and transparency of news sources: data collection and feature analysis. arXiv (2019) ; Aker, A., Kevin, V., Bontcheva, K.: Predicting news source credibility. arXiv (2019) ; Badawy, A., Lerman, K., Ferrara, E.: Who falls for online political manipulation? In: Companion Proceedings of the 2019 World Wide Web Conference, pp. 162–168. ACM (2019) ; Baly, R., Karadzhov, G., Alexandrov, D., Glass, J., Nakov, P.: Predicting factuality of reporting and bias of news media sources. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 3528–3539 (2018) ; Baly, R., Karadzhov, G., Saleh, A., Glass, J., Nakov, P.: Multi-task ordinal regression for jointly predicting the trustworthiness and the leading political ideology of news media. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 2109–2116 (2019) ; Boyd, R.L., et al.: Characterizing the Internet Research Agency's Social Media Operations During the 2016 US ...