Fuzzy-Set Based Sentiment Analysis of Big Social Data

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    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.
    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.
    LanguageEnglish
    Title of host publicationProceedings of the IEEE 18th International Enterprise Distributed Object Computing Conference, EDOC 2014
    EditorsManfred Reichert, Stefanie Rinderle-Ma, Georg Grossmann
    Place of PublicationLos Alamitos, CA
    PublisherIEEE
    Date2014
    Pages71-80
    ISBN (Print)9781479954704
    DOIs
    StatePublished - 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

    Keywords

      Cite this

      Mukkamala, R. R., Hussain, A., & Vatrapu, R. (2014). Fuzzy-Set Based Sentiment Analysis of Big Social Data. In M. Reichert, S. Rinderle-Ma, & G. Grossmann (Eds.), Proceedings of the IEEE 18th International Enterprise Distributed Object Computing Conference, EDOC 2014 (pp. 71-80). Los Alamitos, CA: IEEE. International Enterprise Distributed Object Computing Conference. Proceedings, Vol.. 18, DOI: 10.1109/EDOC.2014.19
      Mukkamala, Raghava Rao ; Hussain, Abid ; Vatrapu, Ravi. / Fuzzy-Set Based Sentiment Analysis of Big Social Data. Proceedings of the IEEE 18th International Enterprise Distributed Object Computing Conference, EDOC 2014. editor / Manfred Reichert ; Stefanie Rinderle-Ma ; Georg Grossmann. Los Alamitos, CA : IEEE, 2014. pp. 71-80 (International Enterprise Distributed Object Computing Conference. Proceedings, ???volume??? 18).
      @inproceedings{429cbb95aa8141d6bcb0c36ece0eed7f,
      title = "Fuzzy-Set Based Sentiment Analysis of Big Social Data",
      abstract = "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",
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      language = "English",
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      Mukkamala, RR, Hussain, A & Vatrapu, R 2014, Fuzzy-Set Based Sentiment Analysis of Big Social Data. in M Reichert, S Rinderle-Ma & G Grossmann (eds), Proceedings of the IEEE 18th International Enterprise Distributed Object Computing Conference, EDOC 2014. IEEE, Los Alamitos, CA, International Enterprise Distributed Object Computing Conference. Proceedings, vol. 18, pp. 71-80, Ulm, Germany, 01/09/2014. DOI: 10.1109/EDOC.2014.19

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

      Proceedings of the IEEE 18th International Enterprise Distributed Object Computing Conference, EDOC 2014. ed. / Manfred Reichert; Stefanie Rinderle-Ma; Georg Grossmann. Los Alamitos, CA : IEEE, 2014. p. 71-80.

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

      TY - GEN

      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 - 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.

      AB - 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.

      KW - Formal methods

      KW - Social data analytics

      KW - Computational social science

      KW - Data science

      KW - Big social data

      U2 - 10.1109/EDOC.2014.19

      DO - 10.1109/EDOC.2014.19

      M3 - Article in proceedings

      SN - 9781479954704

      SP - 71

      EP - 80

      BT - Proceedings of the IEEE 18th International Enterprise Distributed Object Computing Conference, EDOC 2014

      PB - IEEE

      CY - Los Alamitos, CA

      ER -

      Mukkamala RR, Hussain A, Vatrapu R. Fuzzy-Set Based Sentiment Analysis of Big Social Data. In Reichert M, Rinderle-Ma S, Grossmann G, editors, Proceedings of the IEEE 18th International Enterprise Distributed Object Computing Conference, EDOC 2014. Los Alamitos, CA: IEEE. 2014. p. 71-80. (International Enterprise Distributed Object Computing Conference. Proceedings, Vol. 18). Available from, DOI: 10.1109/EDOC.2014.19