Conceptual frameworks for social and cultural Big Data analytics

Answering the epistemological challenge

Bibliographic Data

ID5260992
AuthorsLucy Resnyansky (0000-0003-0583-8163, Defence Science and Technology Group, corresponding author)
Year2019
Volume6
Issue1
Pages205395171882381
Publication date2019-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBig Data & Society (JOURNAL)
Journal identifiersISSN: 2053-9517 • E-ISSN: 2053-9517
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/2053951718823815
OpenAlexW2912904513
LanguageEN
Citations received8
References cited78

This paper aims to contribute to the development of tools to support an analysis of Big Data as manifestations of social processes and human behaviour. Such a task demands both an understanding of the epistemological challenge posed by the Big Data phenomenon and a critical assessment of the offers and promises coming from the area of Big Data analytics. This paper draws upon the critical social and data scientists' view on Big Data as an epistemological challenge that stems not only from the sheer volume of digital data but, predominantly, from the proliferation of the narrow-technological and the positivist views on data. Adoption of the social-scientific epistemological stance presupposes that digital data was conceptualised as manifestations of the social. In order to answer the epistemological challenge, social scientists need to extend the repertoire of social scientific theories and conceptual frameworks that may inform the analysis of the social in the age of Big Data. However, an 'epistemological revolution' discourse on Big Data may hinder the integration of the social scientific knowledge into the Big Data analytics

Analytics · Big data · Data science · Epistemology · Positivism · Social epistemology · Social science · Sociology · Computational and Text Analysis Methods · Computer Science · Data Visualization and Analytics · Ethics and Social Impacts of AI

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Open DOISci-HubOpen Access