Making sense of self-reported socially significant data using computational methods

Burnap, Peter ORCID: https://orcid.org/0000-0003-0396-633X, Avis, Nicholas John and Rana, Omer Farooq ORCID: https://orcid.org/0000-0003-3597-2646 2013. Making sense of self-reported socially significant data using computational methods. International Journal of Social Research Methodology 16 (3) , pp. 215-230. 10.1080/13645579.2013.774174

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Abstract

The growing number of people using social media to communicate with their peers and document their personal everyday feelings and views is creating a ‘data on an epic scale’ that provides the opportunity for social scientists to con- duct research such as ethnography, discourse and content analysis of social interactions, providing an additional insight into today’s society. However, the tools and methods required to conduct such analysis are often isolated and/or proprietary. The Cardiff Online Social Media Observatory (COSMOS) provides an integrated virtual research environment for supporting the collection, analysis, and visualization of social media data, providing researchers with an innovative facility on which to conduct hypothetical experiments that lead to defensible results. This study presents a methodology for Digital Social Research and explains how the features of COSMOS aim to underpin it.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics Social Sciences (Includes Criminology and Education)
Subjects:	H Social Sciences > HV Social pathology. Social and public welfare Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords:	COSMOS, social media data, computational methods, empirical crisis
Publisher:	Taylor & Francis
ISSN:	1364-5579
Funders:	ESRC
Last Modified:	10 Nov 2022 12:56
URI:	https://orca.cardiff.ac.uk/id/eprint/47026

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