Social Data Analytics Tool: Design, Development and Demonstrative Case Studies

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    Abstract

    This paper presents the design, development and demonstrative case studies of the Social Data Analytics Tool, SODATO. Adopting Action Design Framework [1], the objective of SODATO [2] is to collect, store, analyze, and report big social data emanating from the social media engagement of and social media conversations about organizations. We report and discuss results from two demonstrative case studies that were conducted using SODATO and conclude with implications and future work.
    Original languageEnglish
    Title of host publicationProceedings. IEEE 18th International Enterprise Distributed Object Computing. Workshops and Demonstrations, EDOC 2014
    EditorsGeorg Grossmann, Sylvain Hallé, Dimka Karastoyanova, Manfred Reichert, Stefanie Rinderle-Ma
    Number of pages5
    Place of PublicationLos Alamitos, CA
    PublisherIEEE
    Publication date2014
    Pages414-417
    Article number6975394
    ISBN (Print)9781479954704
    DOIs
    Publication statusPublished - 2014
    EventThe 18th IEEE Enterprise Computing Conference. EDOC 2014: Utilizing Big Data for the Enterprise of the Future - Ulm, Germany
    Duration: 1 Sep 20145 Sep 2014
    Conference number: 18
    http://www.edoc2014.org/

    Conference

    ConferenceThe 18th IEEE Enterprise Computing Conference. EDOC 2014
    Number18
    CountryGermany
    CityUlm
    Period01/09/201405/09/2014
    Internet address
    SeriesInternational Enterprise Distributed Object Computing Conference. Proceedings
    Volume18
    ISSN1541-7719

    Bibliographical note

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    Cite this

    Hussain, A., & Vatrapu, R. (2014). Social Data Analytics Tool: Design, Development and Demonstrative Case Studies. In G. Grossmann, S. Hallé, D. Karastoyanova, M. Reichert, & S. Rinderle-Ma (Eds.), Proceedings. IEEE 18th International Enterprise Distributed Object Computing. Workshops and Demonstrations, EDOC 2014 (pp. 414-417). [6975394] IEEE. International Enterprise Distributed Object Computing Conference. Proceedings, Vol.. 18 https://doi.org/10.1109/EDOCW.2014.70