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

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    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.
    Original 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
    Number of pages10
    Place of PublicationLos Alamitos, CA
    Publication date2015
    Article number7364036
    ISBN (Print)9781479999255
    ISBN (Electronic)9781479999255
    Publication statusPublished - 2015
    EventThird IEEE International Conference on Big Data. IEEE BigData 2015 - Hyatt Regency, Santa Clara, CA, United States
    Duration: 29 Oct 20151 Nov 2015
    Conference number: 3


    ConferenceThird IEEE International Conference on Big Data. IEEE BigData 2015
    LocationHyatt Regency
    Country/TerritoryUnited States
    CitySanta Clara, CA
    Internet address

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