Fuzzy-Set Based Sentiment Analysis of Big Social Data

    Publikation: Bidrag til konferencePaperForskningpeer review

    Resumé

    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.

    Konference

    KonferenceThe 18th IEEE Enterprise Computing Conference. EDOC 2014
    Nummer18
    LandTyskland
    ByUlm
    Periode01/09/201405/09/2014
    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). Fuzzy-Set Based Sentiment Analysis of Big Social Data. Afhandling præsenteret på The 18th IEEE Enterprise Computing Conference. EDOC 2014, Ulm, Tyskland.
    Mukkamala, Raghava Rao ; Hussain, Abid ; Vatrapu, Ravi. / Fuzzy-Set Based Sentiment Analysis of Big Social Data. Afhandling præsenteret på The 18th IEEE Enterprise Computing Conference. EDOC 2014, Ulm, Tyskland.10 s.
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    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/",

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    Mukkamala, RR, Hussain, A & Vatrapu, R 2014, 'Fuzzy-Set Based Sentiment Analysis of Big Social Data' Paper fremlagt ved The 18th IEEE Enterprise Computing Conference. EDOC 2014, Ulm, Tyskland, 01/09/2014 - 05/09/2014, .

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

    2014. Afhandling præsenteret på The 18th IEEE Enterprise Computing Conference. EDOC 2014, Ulm, Tyskland.

    Publikation: Bidrag til konferencePaperForskningpeer 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. Afhandling præsenteret på The 18th IEEE Enterprise Computing Conference. EDOC 2014, Ulm, Tyskland.