Predicting Controversial News Using Facebook Reactions

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    Abstract

    Different events and their re- ception in different reader communities may give rise to controversy. We pro- pose a distant supervised entropy-based model that uses Facebook reactions as proxies for predicting news controversy. We prove the validity of this approach by running within- and across-source exper- iments, where different news sources are conceived to approximately correspond to different reader communities. Contextu- ally, we also present and share an au- tomatically generated corpus for contro- versy prediction in Italian.
    Original languageEnglish
    Title of host publicationProceedings of the Fourth Italian Conference on Computational Linguistics (CLiC-it 2017)
    Publication statusPublished - 2017
    EventCLiC-it 2017
    : Italian Conference on Computational Linguistics
    - Rome, Italy
    Duration: 11-Dec-201713-Dec-2017

    Conference

    ConferenceCLiC-it 2017
    CountryItaly
    CityRome
    Period11/12/201713/12/2017

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