Automated dialog analysis to predict blogger community response to newcomer inquiries

Nicolae Nistor, Mihai Dascalu, Yvonne Serafin, Stefan Trausan-Matu

    Research output: Contribution to journalArticleAcademicpeer-review

    Abstract

    Informal learning in online knowledge building communities (OKBCs) often starts with online academic help seeking, and with visitor inquiries on specific topics. In such a context, learning presupposes adequate OKBC response. Employing a social learning analytics approach based on natural language processing and Bakhtin's theory of dialogism, this study aims to predict blogger OKBC response. Manipulating the blog topic (well-defined vs. ill-defined) and the visitor inquiry format (off-topic vs. on-topic), a field experiment with a 2 x 2 factorial design was conducted on a sample of N = 68 blogger communities with a total of 25,303 members. For the entire sample, the community response was influenced only by the inquiry format. In a separate examination of the experimental groups, however, this remained true only for the well-defined topic, whereas for the ill-defined topic the community response only depended on the previously established dialog quality. The findings suggest identification criteria for responsive communities, which can support newcomer integration in OKBCs and, from a larger perspective, the use of OKBCs as components of formal learning environments.

    Original languageEnglish
    Pages (from-to)349–354
    Number of pages6
    JournalComputers in Human Behavior
    Volume89
    Issue number2018
    DOIs
    Publication statusPublished - Dec 2018

    Fingerprint

    Learning
    Blogs
    Blogging
    Natural Language Processing
    Processing
    Experiments
    Newcomers
    Knowledge Building
    Social Learning

    Keywords

    • Online knowledge building communities
    • Newcomer integration
    • Social learning analytics
    • Dialog analysis
    • Academic help seeking
    • ONLINE COMMUNITIES
    • NETWORK ANALYSIS
    • HELP-SEEKING
    • PARTICIPATION
    • INTERVAL
    • SUPPORT

    Cite this

    Nistor, Nicolae ; Dascalu, Mihai ; Serafin, Yvonne ; Trausan-Matu, Stefan. / Automated dialog analysis to predict blogger community response to newcomer inquiries. In: Computers in Human Behavior. 2018 ; Vol. 89, No. 2018. pp. 349–354.
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    abstract = "Informal learning in online knowledge building communities (OKBCs) often starts with online academic help seeking, and with visitor inquiries on specific topics. In such a context, learning presupposes adequate OKBC response. Employing a social learning analytics approach based on natural language processing and Bakhtin's theory of dialogism, this study aims to predict blogger OKBC response. Manipulating the blog topic (well-defined vs. ill-defined) and the visitor inquiry format (off-topic vs. on-topic), a field experiment with a 2 x 2 factorial design was conducted on a sample of N = 68 blogger communities with a total of 25,303 members. For the entire sample, the community response was influenced only by the inquiry format. In a separate examination of the experimental groups, however, this remained true only for the well-defined topic, whereas for the ill-defined topic the community response only depended on the previously established dialog quality. The findings suggest identification criteria for responsive communities, which can support newcomer integration in OKBCs and, from a larger perspective, the use of OKBCs as components of formal learning environments.",
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    Automated dialog analysis to predict blogger community response to newcomer inquiries. / Nistor, Nicolae; Dascalu, Mihai; Serafin, Yvonne; Trausan-Matu, Stefan.

    In: Computers in Human Behavior, Vol. 89, No. 2018, 12.2018, p. 349–354.

    Research output: Contribution to journalArticleAcademicpeer-review

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