Social Set Analysis: A Set Theoretical Approach to Big Data Analytics

Abstract

Current analytical approaches in computational social science can be characterized by four dominant paradigms: text analysis (information extraction and classification), social network analysis (graph theory), social complexity analysis (complex systems science), and social simulations (cellular automata and agent-based modeling). However, when it comes to organizational and societal units of analysis, there exists no approach to conceptualize, model, analyze, explain, and predict social media interactions as individuals' associations with ideas, values, identities, and so on. To address this limitation, based on the sociology of associations and the mathematics of set theory, this paper presents a new approach to big data analytics called social set analysis. Social set analysis consists of a generative framework for the philosophies of computational social science, theory of social data, conceptual and formal models of social data, and an analytical framework for combining big social data sets with organizational and societal data sets. Three empirical studies of big social data are presented to illustrate and demonstrate social set analysis in terms of fuzzy set-theoretical sentiment analysis, crisp set-theoretical interaction analysis, and eventstudies-oriented set-theoretical visualizations. Implications for big data analytics, current limitations of the set-theoretical approach, and future directions are outlined.INDEX TERMS Big social data, formal models, social set analysis, big data visual analytics, new computational models for big social data.

Buzz vs. Sales: Big Social Data Analytics of Style Icon Campaigns and Fashion Designer Collaborations on H&Ms Facebook Page

“…Our findings support existing empirical work that shows a connection between big social data and business data [25]. Particularly, our findings show that there is a connection between social buzz and sales.…”

“…One would believe that less famous designers would "need" more promotion than the more "universal" icons, but it is not the case. P 4 -Style icons target a more differentiated audience than designer collaborations: To understand relationship between audiences of the different style collections, we have employed the method of Social Set Analysis [25] and created three different Venn diagrams. Figure 6(a) shows the overlap between users who have acted (posted, commented or liked) on both style icon campaigns and designer collaborations.…”

Twitter User’s Hobby Estimation Based on Sequential Statements Using Deep Neural Networks

“…There are a lot of existing studies of analysis of big data on Internet or social media [19]- [25]. These studies commonly focus on how to extract information from large amounts of data in formats that can be easily recognized by humans or how to analyze emotions and opinions from such large data.…”

“…Vatrapu et al [25] proposed a social set analysis. This approach consists of a generative framework for the philosophies of computational social science, etc.…”

RKE-CP: Response-based Knowledge Extraction from Collaborative Platform of Text-based Communication

“…A treebased mechanism for identifying the interaction of a person was introduced by Chang et al [13] by representing semantics, context, and syntactic data over a convolution kernel. A problem of higher dimension of text mining over cloud-based big data was introduced by Vatrapu et al [14]. An analysis of social set is presented that uses set theory and big data in order to understand the significance in contextual terms involved in user-defined responses.…”