Close encounters of the conceptual kind: Disambiguating social structure from text
Author(s) -
Timothy R. Hannigan
Publication year - 2015
Publication title -
big data and society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.244
H-Index - 37
ISSN - 2053-9517
DOI - 10.1177/2053951715608655
Subject(s) - big data , data science , extant taxon , epistemology , topic model , sociology , computer science , artificial intelligence , data mining , evolutionary biology , philosophy , biology
Despite its empirical prominence, there is very little extant organizational research on Big Data. However, there is reason to believe this is changing as organizational theory scholars are beginning to embrace new methods and data sources. In this essay, I present a view that suggests there are several latent opportunities, many of which have been simmering unattended for some time. This research approach is not without its challenges, as the ontological terrain of Big Data is untested and potentially disruptive. However, we are observing a renewal of approaches to text and content analysis. By opening up the toolkit of computational linguistics methods for text analysis, Big Data may bring about fresh synthesis and reshape classic debates around social structure
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