Knowing the Tweeters: Deriving sociologically relevant demographics from Twitter

Sloan, Luke ORCID: https://orcid.org/0000-0002-9458-9332, Morgan, Jeffrey, Housley, William ORCID: https://orcid.org/0000-0003-1568-9093, Williams, Matthew Leighton ORCID: https://orcid.org/0000-0003-2566-6063, Edwards, Adam Michael ORCID: https://orcid.org/0000-0002-1332-5934, Burnap, Peter ORCID: https://orcid.org/0000-0003-0396-633X and Rana, Omer Farooq ORCID: https://orcid.org/0000-0003-3597-2646 2013. Knowing the Tweeters: Deriving sociologically relevant demographics from Twitter. Sociological Research Online 18 (3) , 7. 10.5153/sro.3001

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Abstract

A perennial criticism regarding the use of social media in social science research is the lack of demographic information associated with naturally occurring mediated data such as that produced by Twitter. However the fact that demographics information is not explicit does not mean that it is not implicitly present. Utilising the Cardiff Online Social Media ObServatory (COSMOS) this paper suggests various techniques for establishing or estimating demographic data from a sample of more than 113 million Twitter users collected during July 2012. We discuss in detail the methods that can be used for identifying gender and language and illustrate that the proportion of males and females using Twitter in the UK reflects the gender balance observed in the 2011 Census. We also expand on the three types of geographical information that can be derived from Tweets either directly or by proxy and how spatial information can be used to link social media with official curated data. Whilst we make no grand claims about the representative nature of Twitter users in relation to the wider UK population, the derivation of demographic data demonstrates the potential of new social media (NSM) for the social sciences. We consider this paper a clarion call and hope that other researchers test the methods we suggest and develop them further.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Cardiff Centre for Crime, Law and Justice (CCLJ) Computer Science & Informatics Social Sciences (Includes Criminology and Education)
Subjects:	H Social Sciences > HT Communities. Classes. Races Q Science > QA Mathematics > QA76 Computer software
Uncontrolled Keywords:	New Social Media, Demographics, Twitter, Social Media Analytics, Social Science, Sampling
Publisher:	Sociological Research Online
ISSN:	1360-7804
Funders:	ESRC
Last Modified:	23 Oct 2023 15:16
URI:	https://orca.cardiff.ac.uk/id/eprint/49152

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