Adapting computational text analysis to social science (and vice versa)

Paul DiMaggio

    Research output: Contribution to journalComment/debate

    Abstract

    Social scientists and computer scientist are divided by small differences in perspective and not by any significant disciplinary divide. In the field of text analysis, several such differences are noted: social scientists often use unsupervised models to explore corpora, whereas many computer scientists employ supervised models to train data; social scientists hold to more conventional causal notions than do most computer scientists, and often favor intense exploitation of existing algorithms, whereas computer scientists focus more on developing new models; and computer scientists tend to trust human judgment more than social scientists do. These differences have implications that potentially can improve the practice of social science.

    Original languageEnglish (US)
    JournalBig Data and Society
    Volume2
    Issue number2
    DOIs
    StatePublished - 2015

    Keywords

    • Topic models
    • interpretation
    • sentiment analysis
    • supervised models
    • text analysis
    • unsupervised models

    ASJC Scopus subject areas

    • Computer Science Applications
    • Information Systems
    • Information Systems and Management
    • Communication
    • Library and Information Sciences

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