Factweet: Profiling fake news twitter accounts

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Abstract

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.

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APA

Ghanem, B., Ponzetto, S. P., & Rosso, P. (2020). Factweet: Profiling fake news twitter accounts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12379 LNAI, pp. 35–45). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59430-5_3

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