Jeitziner, Loris Tizian

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Jeitziner
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Loris Tizian
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Jeitziner, Loris Tizian

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2023 - 20244
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  • Vorschaubild
    Publikation
    Zooming in: The role of nonverbal behavior in sensing the quality of collaborative group engagement
    (Springer, 16.05.2024) Paneth, Lisa; Jeitziner, Loris Tizian; Rack, Oliver; Opwis, Klaus; Zahn, Carmen [in: International Journal of Computer-Supported Collaborative Learning]
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Affect in science communication: a data-driven analysis of TED Talks on YouTube
    (Springer, 2024) Fischer, Olivia; Jeitziner, Loris Tizian; Wulff, Dirk U. [in: Humanities and Social Sciences Communications]
    Science communication is evolving: Increasingly, it is directed at the public rather than academic peers. Understanding the circumstances under which the public engages with scientific content is therefore crucial to improving science communication. In this article, we investigate the role of affect on audience engagement with a modern form of science communication: TED Talks on the social media platform YouTube. We examined how two aspects of affect, valence and density are associated with public engagement with the talk in terms of popularity (reflecting views and likes) and polarity (reflecting dislikes and comments). We found that the valence of TED Talks was associated with both popularity and polarity: Positive valence was linked to higher talk popularity and lower talk polarity. Density, on the other hand, was only associated with popularity: Higher affective density was linked to higher popularity—even more so than valence—but not polarity. Moreover, the association between affect and engagement was moderated by talk topic, but not by whether the talk included scientific content. Our results establish affect as an important covariate of audience engagement with scientific content on social media, which science communicators may be able to leverage to steer engagement and increase reach.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Exploring linguistic indicators of social collaborative group engagement
    (International Society of the Learning Sciences, 2023) Jeitziner, Loris Tizian; Paneth, Lisa; Rack, Oliver; Zahn, Carmen; Wulff, Dirk U.; Damşa, Crina; Borge, Marcela; Koh, Elizabeth; Worsley, Marcelo [in: Proceedings of the 16th International Conference on Computer-Supported Collaborative Learning - CSCL 2023]
    This study takes a NLP approach to measuring social engagement in CSCL-learning groups. Specifically, we develop linguistic markers to capture aspects of social engagement, namely sentiment, responsiveness and uniformity of participation and compare them to human ratings of social engagement. We observed small to moderate links between NLP-markers and human ratings that varied in size and direction across the different groups. We discuss measurement and prediction of social collaborative group engagement using natural language processing.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    A multi-method approach to capture quality of collaborative group engagement
    (International Society of the Learning Sciences, 2023) Paneth, Lisa; Jeitziner, Loris Tizian; Rack, Oliver; Zahn, Carmen; Damsa, Crina; Borge, Marcela; Koh, Elizabeth; Worsley, Marcelo [in: Proceedings of the 16th International Conference on Computer-Supported Collaborative Learning - CSCL 2023]
    Multi-method approaches are an emerging trend in CSCL research as they allow to paint a more comprehensive picture of complex group learning processes than using a single method. In this contribution, we combined measures from different data sources to capture the quality of collaborative group engagement (QCGE) in CSCL-groups: QCGE-self-assessments, QCGE-ratings of verbal group communication, and video recorded nonverbal group behaviors. Using different methods of analysis, we visualized, described, and analyzed the data and related the measures to each other. Here, we present results suggesting that measures from different data sources are interrelated: For instance, nonverbal behavior (like nodding the head) is related to high QCGE-ratings of verbal communications. Results are preliminary and show disparities, too. Yet, we conclude that the multi-method approach results in a more comprehensive understanding of QCGE. Feasibility and suitability of the multi-method approach are discussed and conclusions for future research are drawn.
    04B - Beitrag Konferenzschrift