Towards a Set Theoretical Approach to Big Data Analytics

    Publikation: Bidrag til konferencePaperForskningpeer review

    Resumé

    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.
    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.

    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

    Citer dette

    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.
    Mukkamala, Raghava Rao ; Hussain, Abid ; Vatrapu, Ravi. / Towards a Set Theoretical Approach to Big Data Analytics. Afhandling præsenteret på 3rd IEEE International Congress on Big Data, Anchorage, USA.8 s.
    @conference{b236fe3a08d641c3a2e903979952d886,
    title = "Towards a Set Theoretical Approach to Big Data Analytics",
    abstract = "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.",
    keywords = "Formal Methods, Social Data Analytics, Computational Social Science, Data Science, Big Social Data",
    author = "Mukkamala, {Raghava Rao} and Abid Hussain and Ravi Vatrapu",
    year = "2014",
    language = "English",
    note = "null ; Conference date: 27-06-2014 Through 02-07-2014",
    url = "http://www.ieeebigdata.org/2014/index.html",

    }

    Mukkamala, RR, Hussain, A & Vatrapu, R 2014, 'Towards a Set Theoretical Approach to Big Data Analytics' Paper fremlagt ved 3rd IEEE International Congress on Big Data, Anchorage, USA, 27/06/2014 - 02/07/2014, .

    Towards a Set Theoretical Approach to Big Data Analytics. / Mukkamala, Raghava Rao; Hussain, Abid; Vatrapu, Ravi.

    2014. Afhandling præsenteret på 3rd IEEE International Congress on Big Data, Anchorage, USA.

    Publikation: Bidrag til konferencePaperForskningpeer review

    TY - CONF

    T1 - Towards a Set Theoretical Approach to Big Data Analytics

    AU - Mukkamala,Raghava Rao

    AU - Hussain,Abid

    AU - Vatrapu,Ravi

    PY - 2014

    Y1 - 2014

    N2 - 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.

    AB - 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.

    KW - Formal Methods

    KW - Social Data Analytics

    KW - Computational Social Science

    KW - Data Science

    KW - Big Social Data

    M3 - Paper

    ER -

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