Towards a Set Theoretical Approach to Big Data Analytics

Raghava Rao Mukkamala, Abid Hussain, Ravi Vatrapu

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


Formal methods, models and tools for social big data analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by relational sociology. There are no other unified modeling approaches to social big data that integrate the conceptual, formal and software 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 set theory and discuss the 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 and last, based on the formal model and sentiment analysis of text, we present a method for profiling of artifacts and actors and apply this technique to the data analysis of big social data collected from Facebook page of the fast fashion company, H&M.
Original languageEnglish
Title of host publicationBig Data (BigData Congress), 2014 IEEE International Congress on
Publication date27 Jun 2014
ISBN (Print)978-1-4799-5056-0
Publication statusPublished - 27 Jun 2014
Event2014 IEEE International Congress on Big Data - Anchorage, Alaska, United States
Duration: 27 Jun 20142 Jul 2014
Conference number: 3


Conference2014 IEEE International Congress on Big Data
Country/TerritoryUnited States
CityAnchorage, Alaska
Internet address


  • Formal Methods
  • Social Data Analytics
  • Computational Social Science
  • Data Science
  • Big Social Data


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