emotionVis: Designing an Emotion Text Inference Tool for Visual Analytics

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

    Abstrakt

    With increasingly high volumes of conversations across social media, the rapid detection of emotions is of significant strategic value to industry practitioners. Summarizing large volumes of text with computational linguistics and visual analytics allows for several new possibilities from general trend detection to specific applications in marketing practice, such as monitoring product launches, campaigns and public relations milestones. After collecting 1.6 million user-tagged feelings from 12 million online posts that mention emotions, we utilized machine learning techniques towards building an automatic ‘feelings meter’; a tool for both researchers and practitioners to automatically detect emotional dimensions from text. Following several iterations, the test version has now taken shape as emotionVis, a dashboard prototype for inferring emotions from text while presenting the results for visual analysis.
    OriginalsprogEngelsk
    TitelTackling Society’s Grand Challenges with Design Science : Proceedings of the 11th International Conference, DESRIST 2016
    RedaktørerJeffrey Parsons, Tuure Tuunanen, John Venable, Brian Donnellan, Markus Helfert, Jim Kenneally
    UdgivelsesstedChams
    ForlagSpringer Science+Business Media
    Publikationsdato2016
    Sider238–244
    ISBN (Trykt)9783319392936
    ISBN (Elektronisk)9783319392943
    DOI
    StatusUdgivet - 2016
    BegivenhedThe 11th International Conference on Design Science Research in Information Systems and Technology. DESRIST 2016 - St. John’s, NL, Canada
    Varighed: 23 maj 201625 jun. 2016
    Konferencens nummer: 11
    https://desrist2016.wordpress.com/

    Konference

    KonferenceThe 11th International Conference on Design Science Research in Information Systems and Technology. DESRIST 2016
    Nummer11
    LandCanada
    BySt. John’s, NL
    Periode23/05/201625/06/2016
    Internetadresse
    NavnLecture Notes in Computer Science
    Vol/bind9661
    ISSN0302-9743

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