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

机译:社交集Visualizer:一种落实真实赛事大社会数据分析的理论方法

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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.
机译:大型社会数据分析中的目前最先进的是,基本上限于建立社会哲学方法的社会哲学方法所了解的理论方法,如社会网络分析(SNA)。本文提出并说明了大社会数据分析,社会集分析(SSA)的替代整体方法,这是基于协会社会学,集合理论的数学和事件研究的高级视觉分析。我们通过将其应用于与社交媒体平台上的用户互动方面的反思,通过将其申请将现实世界事件与其反思联系起来的新方法。我们展示并讨论了社会数据的理论和概念模型,然后是根据Facebook的真实社交数据示例的基于集合理论和事件研究的技术的正式描述。然后,我们通过报告设计,开发和评估结果来说明我们最先进的视觉分析仪表板,社交集可视化器(Sosevi)的设计,开发和评估结果。使用Sosevi,我们进行了一个真实的案例研究,由传统媒体中提到的11个不同公司组成了大约9000万的Facebook用户互动,这些公司在孟加拉国的服装厂事故中提到,并分析了结果。仪表板的企业应用程序域是企业社会责任(CSR),目标最终用户是CSR研究人员和从业者。仪表板的设计基于上述计算社会科学的社会集分析方法。仪表板的开发涉及尖端开源视觉分析库(D3.JS)以及跨时间和空间,会话彗星和更多的演员移动性的创建新的可视化。仪表板的评估包括与CSR学生的技术测试,可用性测试和特定于域的测试,并产生了积极的结果。总之,我们讨论了社会集分析的新分析方法,并讨论了基于社会哲学方法的设定理论方法的益处。

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