%0 Journal Article
%T Conceptual frameworks for social and cultural Big Data analytics: Answering the epistemological challenge
%A Lucy Resnyansky
%J Big Data & Society
%@ 2053-9517
%D 2019
%R 10.1177/2053951718823815
%X 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
%K Social and cultural Big Data analytics
%K social science
%K computational science
%K epistemological challenge
%K social media
%U https://journals.sagepub.com/doi/full/10.1177/2053951718823815