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Towards a set Theoretical Approach to Big Data Analytics

Publication: Research - peer-reviewArticle in proceedings

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.

Publication information

Original languageEnglish
Title of host publicationProceedings of the 2014 IEEE International Congress on Big Data. BigData Congress 2014
EditorsPeter Chen, Hermant Jain
Place of PublicationLos Alamitos, CA
PublisherIEEE
Publication date2014
Pages629-636
ISBN (print)9781479950577
DOIs
StatePublished - 2014
Event - Anchorage, United States

Conference

Conference3rd IEEE International Congress on Big Data
Nummer3
LandUnited States
ByAnchorage
Periode27/06/201402/07/2014
Internetadresse

ID: 42802094