Towards a Set Theoretical Approach to Big Data Analytics

    Research output: Contribution to conferencePaperResearchpeer-review

    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.
    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.

    Conference

    Conference3rd IEEE International Congress on Big Data
    Number3
    CountryUnited States
    CityAnchorage
    Period27/06/201402/07/2014
    Internet address

    Keywords

      Cite this

      Mukkamala, R. R., Hussain, A., & Vatrapu, R. (2014). Towards a Set Theoretical Approach to Big Data Analytics. Paper presented at 3rd IEEE International Congress on Big Data, Anchorage, United States.
      Mukkamala, Raghava Rao ; Hussain, Abid ; Vatrapu, Ravi. / Towards a Set Theoretical Approach to Big Data Analytics. Paper presented at 3rd IEEE International Congress on Big Data, Anchorage, United States.8 p.
      @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 presented at, Anchorage, United States, 27/06/2014 - 02/07/2014, .

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

      2014. Paper presented at 3rd IEEE International Congress on Big Data, Anchorage, United States.

      Research output: Contribution to conferencePaperResearchpeer-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. Paper presented at 3rd IEEE International Congress on Big Data, Anchorage, United States.