Predicting the Factuality of Reporting of News Media Using Observations About User Attention in Their YouTube Channels
Autor: | Bozhanova, Krasimira, Dinkov, Yoan, Koychev, Ivan, Castaldo, Maria, Venturini, Tommaso, Nakov, Preslav |
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Rok vydání: | 2021 |
Předmět: | |
Zdroj: | RANLP-2021 |
Druh dokumentu: | Working Paper |
Popis: | We propose a novel framework for predicting the factuality of reporting of news media outlets by studying the user attention cycles in their YouTube channels. In particular, we design a rich set of features derived from the temporal evolution of the number of views, likes, dislikes, and comments for a video, which we then aggregate to the channel level. We develop and release a dataset for the task, containing observations of user attention on YouTube channels for 489 news media. Our experiments demonstrate both complementarity and sizable improvements over state-of-the-art textual representations. Comment: Factuality, disinformation, misinformation, fake news, Youtube channels, propaganda, attention cycles |
Databáze: | arXiv |
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