Doing social media analytics. Issue 2 (July 2016)

• Record Type: Journal Article
• Authors: Brooker, Phillip; Barnett, Julie; Cribbin, Timothy
• Is Part Of: Big data & society. Volume 3:Issue 2(2016)
• Publication Date: 2016-07
• Subjects: Social media -- Twitter -- analytics -- digital social science -- data visualisation -- methods; Big data -- Social aspects -- Periodicals; Social sciences -- Research -- Data processing -- Periodicals; Social sciences -- Research -- Methodology -- Periodicals; Data mining -- Periodicals; 300.28557
• DOI: 10.1177/2053951716658060
• Languages: English
• ISSNs: 2053-9517

Abstract

In the few years since the advent of 'Big Data' research, social media analytics has begun to accumulate studies drawing on social media as a resource and tool for research work. Yet, there has been relatively little attention paid to the development of methodologies for handling this kind of data. The few works that exist in this area often reflect upon the implications of 'grand' social science methodological concepts for new social media research (i.e. they focus on general issues such as sampling, data validity, ethics, etc.). By contrast, we advance an abductively oriented methodological suite designed to explore the construction of phenomena played out through social media. To do this, we use a software tool – Chorus – to illustrate a visual analytic approach to data. Informed by visual analytic principles, we posit a two-by-two methodological model of social media analytics, combining two data collection strategies with two analytic modes. We go on to demonstrate each of these four approaches 'in action', to help clarify how and why they might be used to address various research questions.