Towards a Set Theoretical Approach to Big Data Analytics

    Publikation: KonferencebidragPaperForskningpeer review

    Abstrakt

    Formal methods, models and tools for social big data analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by relational sociology. There are no other unified modeling approaches to social big data that integrate the conceptual, formal and software realms. In this paper, we first present and discuss a theory and conceptual model of social data. Second, we outline a formal model based on set theory and discuss the semantics of the formal model with a real-world social data example from Facebook. Third, we briefly present and discuss the Social Data Analytics Tool (SODATO) that realizes the conceptual model in software and provisions social data analysis based on the conceptual and formal models. Fourth and last, based on the formal model and sentiment analysis of text, we present a method for profiling of artifacts and actors and apply this technique to the data analysis of big social data collected from Facebook page of the fast fashion company, H&M.
    OriginalsprogEngelsk
    Publikationsdato2014
    Antal sider8
    StatusUdgivet - 2014
    Begivenhed3rd IEEE International Congress on Big Data: BigData Congress 2014 - Anchorage, USA
    Varighed: 27 jun. 20142 jul. 2014
    Konferencens nummer: 3
    http://www.ieeebigdata.org/2014/index.html

    Konference

    Konference3rd IEEE International Congress on Big Data
    Nummer3
    LandUSA
    ByAnchorage
    Periode27/06/201402/07/2014
    Internetadresse

    Emneord

    • Formal Methods
    • Social Data Analytics
    • Computational Social Science
    • Data Science
    • Big Social Data

    Citationsformater

    Mukkamala, R. R., Hussain, A., & Vatrapu, R. (2014). Towards a Set Theoretical Approach to Big Data Analytics. Afhandling præsenteret på 3rd IEEE International Congress on Big Data, Anchorage, USA.