Selected article for: "art state and propose framework"

Author: Bozhanova, Krasimira; Dinkov, Yoan; Koychev, Ivan; Castaldo, Maria; Venturini, Tommaso; Nakov, Preslav
Title: Predicting the Factuality of Reporting of News Media Using Observations About User Attention in Their YouTube Channels
  • Cord-id: m0bc82k5
  • Document date: 2021_8_27
  • ID: m0bc82k5
    Snippet: 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
    Document: 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.

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