Visual network analysis of twitter data for co-organizing conferences: Case CMAD 2013

J Jussila, J Huhtamäki, K Henttonen, H Kärkkäinen, Kaisa Still

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    9 Citations (Scopus)

    Abstract

    The aim of this research is to explore what kinds of insights information visualization of social media data can provide for co-organizing conferences. Our paper focuses on Twitter use before, during and after conference. We present a case study based on an conference of Community Manager Appreciation Day (CMAD 2013). With the process of data-driven visual network analysis, we used Twitter data to analyse the network of conference participants and the conference's discussion topics. We were able to identify e.g. influential conference participants, most interesting presentations and discussions, similarities between interests of the conference participants. Hence, several development and information needs of conference co-organization were derived from the information visualizations, which have implications for improving the planning and co-organizing of conferences, as well as for Twitter use in conference communication
    Original languageEnglish
    Title of host publicationProceedings
    Subtitle of host publication47th Hawaii International Conference on System Sciences, 2014
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages1474-1483
    ISBN (Print)978-147992504-9
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA4 Article in a conference publication
    Event47th Hawaii International Conference on System Sciences, HICSS 2014 - Waikoloa, HI, United States
    Duration: 6 Jan 20149 Jan 2014

    Conference

    Conference47th Hawaii International Conference on System Sciences, HICSS 2014
    Abbreviated titleHICSS 2014
    CountryUnited States
    CityWaikoloa, HI
    Period6/01/149/01/14

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    Electric network analysis
    Visualization
    Managers
    Planning
    Communication

    Cite this

    Jussila, J., Huhtamäki, J., Henttonen, K., Kärkkäinen, H., & Still, K. (2014). Visual network analysis of twitter data for co-organizing conferences: Case CMAD 2013. In Proceedings: 47th Hawaii International Conference on System Sciences, 2014 (pp. 1474-1483). IEEE Institute of Electrical and Electronic Engineers . https://doi.org/10.1109/HICSS.2014.190
    Jussila, J ; Huhtamäki, J ; Henttonen, K ; Kärkkäinen, H ; Still, Kaisa. / Visual network analysis of twitter data for co-organizing conferences : Case CMAD 2013. Proceedings: 47th Hawaii International Conference on System Sciences, 2014. IEEE Institute of Electrical and Electronic Engineers , 2014. pp. 1474-1483
    @inproceedings{ffae4456436d4e16b2779f4eae73bc7f,
    title = "Visual network analysis of twitter data for co-organizing conferences: Case CMAD 2013",
    abstract = "The aim of this research is to explore what kinds of insights information visualization of social media data can provide for co-organizing conferences. Our paper focuses on Twitter use before, during and after conference. We present a case study based on an conference of Community Manager Appreciation Day (CMAD 2013). With the process of data-driven visual network analysis, we used Twitter data to analyse the network of conference participants and the conference's discussion topics. We were able to identify e.g. influential conference participants, most interesting presentations and discussions, similarities between interests of the conference participants. Hence, several development and information needs of conference co-organization were derived from the information visualizations, which have implications for improving the planning and co-organizing of conferences, as well as for Twitter use in conference communication",
    author = "J Jussila and J Huhtam{\"a}ki and K Henttonen and H K{\"a}rkk{\"a}inen and Kaisa Still",
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    Jussila, J, Huhtamäki, J, Henttonen, K, Kärkkäinen, H & Still, K 2014, Visual network analysis of twitter data for co-organizing conferences: Case CMAD 2013. in Proceedings: 47th Hawaii International Conference on System Sciences, 2014. IEEE Institute of Electrical and Electronic Engineers , pp. 1474-1483, 47th Hawaii International Conference on System Sciences, HICSS 2014, Waikoloa, HI, United States, 6/01/14. https://doi.org/10.1109/HICSS.2014.190

    Visual network analysis of twitter data for co-organizing conferences : Case CMAD 2013. / Jussila, J; Huhtamäki, J; Henttonen, K; Kärkkäinen, H; Still, Kaisa.

    Proceedings: 47th Hawaii International Conference on System Sciences, 2014. IEEE Institute of Electrical and Electronic Engineers , 2014. p. 1474-1483.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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    AU - Kärkkäinen, H

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    AB - The aim of this research is to explore what kinds of insights information visualization of social media data can provide for co-organizing conferences. Our paper focuses on Twitter use before, during and after conference. We present a case study based on an conference of Community Manager Appreciation Day (CMAD 2013). With the process of data-driven visual network analysis, we used Twitter data to analyse the network of conference participants and the conference's discussion topics. We were able to identify e.g. influential conference participants, most interesting presentations and discussions, similarities between interests of the conference participants. Hence, several development and information needs of conference co-organization were derived from the information visualizations, which have implications for improving the planning and co-organizing of conferences, as well as for Twitter use in conference communication

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    Jussila J, Huhtamäki J, Henttonen K, Kärkkäinen H, Still K. Visual network analysis of twitter data for co-organizing conferences: Case CMAD 2013. In Proceedings: 47th Hawaii International Conference on System Sciences, 2014. IEEE Institute of Electrical and Electronic Engineers . 2014. p. 1474-1483 https://doi.org/10.1109/HICSS.2014.190