Fuzzy-Set Based Sentiment Analysis of Big Social Data

    Research output: Contribution to conferencePaperResearchpeer-review

    Abstract

    Computational approaches to social media analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. There are no other unified modelling approaches to social data that integrate the conceptual, formal, software, analytical and empirical 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 fuzzy set theory and describe the operational 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, we use SODATO to fetch social data from the facebook wall of a global brand, H&M and conduct a sentiment classification of the posts and comments. Fifth, we analyse the sentiment classifications by constructing crisp as well as the fuzzy sets of the artefacts (posts, comments, likes, and shares). We document and discuss the longitudinal sentiment profiles of artefacts and actors on the facebook page. Sixth and last, we discuss the analytical method and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.
    Computational approaches to social media analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. There are no other unified modelling approaches to social data that integrate the conceptual, formal, software, analytical and empirical 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 fuzzy set theory and describe the operational 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, we use SODATO to fetch social data from the facebook wall of a global brand, H&M and conduct a sentiment classification of the posts and comments. Fifth, we analyse the sentiment classifications by constructing crisp as well as the fuzzy sets of the artefacts (posts, comments, likes, and shares). We document and discuss the longitudinal sentiment profiles of artefacts and actors on the facebook page. Sixth and last, we discuss the analytical method and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.

    Conference

    ConferenceThe 18th IEEE Enterprise Computing Conference. EDOC 2014
    Number18
    CountryGermany
    CityUlm
    Period01/09/201405/09/2014
    Internet address

    Keywords

      Cite this

      Mukkamala, R. R., Hussain, A., & Vatrapu, R. (2014). Fuzzy-Set Based Sentiment Analysis of Big Social Data. Paper presented at The 18th IEEE Enterprise Computing Conference. EDOC 2014, Ulm, Germany.
      Mukkamala, Raghava Rao ; Hussain, Abid ; Vatrapu, Ravi. / Fuzzy-Set Based Sentiment Analysis of Big Social Data. Paper presented at The 18th IEEE Enterprise Computing Conference. EDOC 2014, Ulm, Germany.10 p.
      @conference{249f02e658b946dcb3de621a46d4ce4f,
      title = "Fuzzy-Set Based Sentiment Analysis of Big Social Data",
      abstract = "Computational approaches to social media analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. There are no other unified modelling approaches to social data that integrate the conceptual, formal, software, analytical and empirical 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 fuzzy set theory and describe the operational 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, we use SODATO to fetch social data from the facebook wall of a global brand, H&M and conduct a sentiment classification of the posts and comments. Fifth, we analyse the sentiment classifications by constructing crisp as well as the fuzzy sets of the artefacts (posts, comments, likes, and shares). We document and discuss the longitudinal sentiment profiles of artefacts and actors on the facebook page. Sixth and last, we discuss the analytical method and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.",
      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: 01-09-2014 Through 05-09-2014",
      url = "http://www.edoc2014.org/",

      }

      Mukkamala, RR, Hussain, A & Vatrapu, R 2014, 'Fuzzy-Set Based Sentiment Analysis of Big Social Data' Paper presented at, Ulm, Germany, 01/09/2014 - 05/09/2014, .

      Fuzzy-Set Based Sentiment Analysis of Big Social Data. / Mukkamala, Raghava Rao; Hussain, Abid; Vatrapu, Ravi.

      2014. Paper presented at The 18th IEEE Enterprise Computing Conference. EDOC 2014, Ulm, Germany.

      Research output: Contribution to conferencePaperResearchpeer-review

      TY - CONF

      T1 - Fuzzy-Set Based Sentiment Analysis of Big Social Data

      AU - Mukkamala,Raghava Rao

      AU - Hussain,Abid

      AU - Vatrapu,Ravi

      PY - 2014

      Y1 - 2014

      N2 - Computational approaches to social media analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. There are no other unified modelling approaches to social data that integrate the conceptual, formal, software, analytical and empirical 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 fuzzy set theory and describe the operational 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, we use SODATO to fetch social data from the facebook wall of a global brand, H&M and conduct a sentiment classification of the posts and comments. Fifth, we analyse the sentiment classifications by constructing crisp as well as the fuzzy sets of the artefacts (posts, comments, likes, and shares). We document and discuss the longitudinal sentiment profiles of artefacts and actors on the facebook page. Sixth and last, we discuss the analytical method and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.

      AB - Computational approaches to social media analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. There are no other unified modelling approaches to social data that integrate the conceptual, formal, software, analytical and empirical 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 fuzzy set theory and describe the operational 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, we use SODATO to fetch social data from the facebook wall of a global brand, H&M and conduct a sentiment classification of the posts and comments. Fifth, we analyse the sentiment classifications by constructing crisp as well as the fuzzy sets of the artefacts (posts, comments, likes, and shares). We document and discuss the longitudinal sentiment profiles of artefacts and actors on the facebook page. Sixth and last, we discuss the analytical method and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.

      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. Fuzzy-Set Based Sentiment Analysis of Big Social Data. 2014. Paper presented at The 18th IEEE Enterprise Computing Conference. EDOC 2014, Ulm, Germany.