Social Set Visualizer: A Set Theoretical Approach to Big Social Data Analytics of Real-world Events

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

    Abstract

    Current state-of-the-art in big social data analytics is largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. This paper proposes and illustrates an alternate holistic approach to big social data analytics, social set analysis (SSA), which is based on the sociology of associations, mathematics of set theory, and advanced visual analytics of event studies. We illustrate our new approach by applying it to relate real-world events with their reflections in terms of user interactions on social media platforms. We present and discuss a theoretical and conceptual model of social data followed by a formal description of our technique based on set theory and event studies with a real-world social data example from Facebook. We then illustrate our new approach by reporting on the design, development, and evaluation results of a state-of-the-art visual analytics dashboard, the Social Set Visualizer (SoSeVi). Using SoSeVi, we conducted a real-world case study that consists of approximately 90 million Facebook user interactions from 11 different companies that have been mentioned in the traditional media in relation to the garment factory accidents in Bangladesh, and analyze the results. The enterprise application domain for the dashboard is corporate social responsibility (CSR) and the targeted end-users are CSR researchers and practitioners. The design of the dashboard was based on the social set analysis approach to computational social science mentioned above. The development of the dashboard involved cutting-edge open source visual analytics libraries (D3.js) and creation of new visualizations such as of actor mobility across time and space, conversational comets, and more. Evaluation of the dashboard consisted of technical testing, usability testing, and domain-specific testing with CSR students and yielded positive results. In conclusion, we discuss the new analytical- approach of social set analysis and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.
    Current state-of-the-art in big social data analytics is largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. This paper proposes and illustrates an alternate holistic approach to big social data analytics, social set analysis (SSA), which is based on the sociology of associations, mathematics of set theory, and advanced visual analytics of event studies. We illustrate our new approach by applying it to relate real-world events with their reflections in terms of user interactions on social media platforms. We present and discuss a theoretical and conceptual model of social data followed by a formal description of our technique based on set theory and event studies with a real-world social data example from Facebook. We then illustrate our new approach by reporting on the design, development, and evaluation results of a state-of-the-art visual analytics dashboard, the Social Set Visualizer (SoSeVi). Using SoSeVi, we conducted a real-world case study that consists of approximately 90 million Facebook user interactions from 11 different companies that have been mentioned in the traditional media in relation to the garment factory accidents in Bangladesh, and analyze the results. The enterprise application domain for the dashboard is corporate social responsibility (CSR) and the targeted end-users are CSR researchers and practitioners. The design of the dashboard was based on the social set analysis approach to computational social science mentioned above. The development of the dashboard involved cutting-edge open source visual analytics libraries (D3.js) and creation of new visualizations such as of actor mobility across time and space, conversational comets, and more. Evaluation of the dashboard consisted of technical testing, usability testing, and domain-specific testing with CSR students and yielded positive results. In conclusion, we discuss the new analytical- approach of social set analysis 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 2015 IEEE International Conference on Big Data
    EditorsHoward Ho, Beng Chin Ooi, Mohammed J. Zaki, Xiaohua Hu, Laura Haas, Vipin Kumar, Sudarsan Rachuri, Shipeng Yu, Morris Hui-I Hsiao, Jian Li, Feng Luo, Saumyadipta Pyne, Kemafor Ogan
    Place of PublicationLos Alamitos, CA
    PublisherIEEE
    Date2015
    Pages2418-2427
    ISBN (Print)9781479999255
    DOIs
    StatePublished - 2015
    Event2015 IEEE International Conference on Big Data - Hyatt Regency, Santa Clara, CA, United States
    Duration: 29 Oct 20151 Nov 2015
    http://cci.drexel.edu/bigdata/bigdata2015/

    Conference

    Conference2015 IEEE International Conference on Big Data
    LocationHyatt Regency
    CountryUnited States
    CitySanta Clara, CA
    Period29/10/201501/11/2015
    Internet address

    Bibliographical note

    CBS Library does not have access to the material

    Cite this

    Flesch, B., Vatrapu, R., Mukkamala, R. R., & Hussain, A. (2015). Social Set Visualizer: A Set Theoretical Approach to Big Social Data Analytics of Real-world Events . In H. Ho, B. C. Ooi, M. J. Zaki, X. Hu, L. Haas, V. Kumar, S. Rachuri, S. Yu, M. H-I. Hsiao, J. Li, F. Luo, S. Pyne, ... K. Ogan (Eds.), Proceedings 2015 IEEE International Conference on Big Data (pp. 2418-2427 ). Los Alamitos, CA: IEEE. DOI: 10.1109/BigData.2015.7364036
    Flesch, Benjamin ; Vatrapu, Ravi ; Mukkamala, Raghava Rao ; Hussain, Abid. / Social Set Visualizer : A Set Theoretical Approach to Big Social Data Analytics of Real-world Events . Proceedings 2015 IEEE International Conference on Big Data. editor / Howard Ho ; Beng Chin Ooi ; Mohammed J. Zaki ; Xiaohua Hu ; Laura Haas ; Vipin Kumar ; Sudarsan Rachuri ; Shipeng Yu ; Morris Hui-I Hsiao ; Jian Li ; Feng Luo ; Saumyadipta Pyne ; Kemafor Ogan. Los Alamitos, CA : IEEE, 2015. pp. 2418-2427
    @inproceedings{6c35219e3cd24b838d8a23a2210ccac9,
    title = "Social Set Visualizer: A Set Theoretical Approach to Big Social Data Analytics of Real-world Events",
    abstract = "Current state-of-the-art in big social data analytics is largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. This paper proposes and illustrates an alternate holistic approach to big social data analytics, social set analysis (SSA), which is based on the sociology of associations, mathematics of set theory, and advanced visual analytics of event studies. We illustrate our new approach by applying it to relate real-world events with their reflections in terms of user interactions on social media platforms. We present and discuss a theoretical and conceptual model of social data followed by a formal description of our technique based on set theory and event studies with a real-world social data example from Facebook. We then illustrate our new approach by reporting on the design, development, and evaluation results of a state-of-the-art visual analytics dashboard, the Social Set Visualizer (SoSeVi). Using SoSeVi, we conducted a real-world case study that consists of approximately 90 million Facebook user interactions from 11 different companies that have been mentioned in the traditional media in relation to the garment factory accidents in Bangladesh, and analyze the results. The enterprise application domain for the dashboard is corporate social responsibility (CSR) and the targeted end-users are CSR researchers and practitioners. The design of the dashboard was based on the social set analysis approach to computational social science mentioned above. The development of the dashboard involved cutting-edge open source visual analytics libraries (D3.js) and creation of new visualizations such as of actor mobility across time and space, conversational comets, and more. Evaluation of the dashboard consisted of technical testing, usability testing, and domain-specific testing with CSR students and yielded positive results. In conclusion, we discuss the new analytical- approach of social set analysis and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.",
    author = "Benjamin Flesch and Ravi Vatrapu and Mukkamala, {Raghava Rao} and Abid Hussain",
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    year = "2015",
    doi = "10.1109/BigData.2015.7364036",
    language = "English",
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    Flesch, B, Vatrapu, R, Mukkamala, RR & Hussain, A 2015, Social Set Visualizer: A Set Theoretical Approach to Big Social Data Analytics of Real-world Events . in H Ho, BC Ooi, MJ Zaki, X Hu, L Haas, V Kumar, S Rachuri, S Yu, MH-I Hsiao, J Li, F Luo, S Pyne & K Ogan (eds), Proceedings 2015 IEEE International Conference on Big Data. IEEE, Los Alamitos, CA, pp. 2418-2427 , Santa Clara, CA, United States, 29/10/2015. DOI: 10.1109/BigData.2015.7364036

    Social Set Visualizer : A Set Theoretical Approach to Big Social Data Analytics of Real-world Events . / Flesch, Benjamin; Vatrapu, Ravi; Mukkamala, Raghava Rao; Hussain, Abid.

    Proceedings 2015 IEEE International Conference on Big Data. ed. / Howard Ho; Beng Chin Ooi; Mohammed J. Zaki; Xiaohua Hu; Laura Haas; Vipin Kumar; Sudarsan Rachuri; Shipeng Yu; Morris Hui-I Hsiao; Jian Li; Feng Luo; Saumyadipta Pyne; Kemafor Ogan. Los Alamitos, CA : IEEE, 2015. p. 2418-2427 .

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

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    AU - Hussain,Abid

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    N2 - Current state-of-the-art in big social data analytics is largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. This paper proposes and illustrates an alternate holistic approach to big social data analytics, social set analysis (SSA), which is based on the sociology of associations, mathematics of set theory, and advanced visual analytics of event studies. We illustrate our new approach by applying it to relate real-world events with their reflections in terms of user interactions on social media platforms. We present and discuss a theoretical and conceptual model of social data followed by a formal description of our technique based on set theory and event studies with a real-world social data example from Facebook. We then illustrate our new approach by reporting on the design, development, and evaluation results of a state-of-the-art visual analytics dashboard, the Social Set Visualizer (SoSeVi). Using SoSeVi, we conducted a real-world case study that consists of approximately 90 million Facebook user interactions from 11 different companies that have been mentioned in the traditional media in relation to the garment factory accidents in Bangladesh, and analyze the results. The enterprise application domain for the dashboard is corporate social responsibility (CSR) and the targeted end-users are CSR researchers and practitioners. The design of the dashboard was based on the social set analysis approach to computational social science mentioned above. The development of the dashboard involved cutting-edge open source visual analytics libraries (D3.js) and creation of new visualizations such as of actor mobility across time and space, conversational comets, and more. Evaluation of the dashboard consisted of technical testing, usability testing, and domain-specific testing with CSR students and yielded positive results. In conclusion, we discuss the new analytical- approach of social set analysis and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.

    AB - Current state-of-the-art in big social data analytics is largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. This paper proposes and illustrates an alternate holistic approach to big social data analytics, social set analysis (SSA), which is based on the sociology of associations, mathematics of set theory, and advanced visual analytics of event studies. We illustrate our new approach by applying it to relate real-world events with their reflections in terms of user interactions on social media platforms. We present and discuss a theoretical and conceptual model of social data followed by a formal description of our technique based on set theory and event studies with a real-world social data example from Facebook. We then illustrate our new approach by reporting on the design, development, and evaluation results of a state-of-the-art visual analytics dashboard, the Social Set Visualizer (SoSeVi). Using SoSeVi, we conducted a real-world case study that consists of approximately 90 million Facebook user interactions from 11 different companies that have been mentioned in the traditional media in relation to the garment factory accidents in Bangladesh, and analyze the results. The enterprise application domain for the dashboard is corporate social responsibility (CSR) and the targeted end-users are CSR researchers and practitioners. The design of the dashboard was based on the social set analysis approach to computational social science mentioned above. The development of the dashboard involved cutting-edge open source visual analytics libraries (D3.js) and creation of new visualizations such as of actor mobility across time and space, conversational comets, and more. Evaluation of the dashboard consisted of technical testing, usability testing, and domain-specific testing with CSR students and yielded positive results. In conclusion, we discuss the new analytical- approach of social set analysis and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.

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    Flesch B, Vatrapu R, Mukkamala RR, Hussain A. Social Set Visualizer: A Set Theoretical Approach to Big Social Data Analytics of Real-world Events . In Ho H, Ooi BC, Zaki MJ, Hu X, Haas L, Kumar V, Rachuri S, Yu S, Hsiao MH-I, Li J, Luo F, Pyne S, Ogan K, editors, Proceedings 2015 IEEE International Conference on Big Data. Los Alamitos, CA: IEEE. 2015. p. 2418-2427 . Available from, DOI: 10.1109/BigData.2015.7364036