Understanding micro-processes of community building and mutual learning on Twitter: a ‘small data’ approach

Abstract

This article contributes to an emerging field of 'small data' research on Twitter by presenting a case study of how teachers and students at a sixth-form college in the north of England used this social media platform to help construct a 'community of practice' that enabled micro-processes of recognition and mutual learning. Conducted as part of a broader action research project that focused on the 'digital story circle' as a site of, and for, narrative exchange and knowledge production, this study takes the form of a detailed analysis of a departmental Twitter account, combining basic quantitative metrics, close reading of selected Twitter data and qualitative interviews with teachers and students. Working with (and sometimes against) Twitter's platform architecture, teachers and students constructed, through distinct patterns of use, a shared space for dialogue that facilitated community building within the department. On the whole, they were able to overcome justified anxieties about professionalism and privacy; this was achieved by building on high levels of pre-existing trust among staff and by performing that mutual trust online through personal modes of communication. Through micro-processes of recognition and a breaking down of conventional hierarchies that affirmed students' agency as knowledge producers, the departmental Twitter account enabled mutual learning beyond curriculum and classroom. The significance of such micro-processes could only have been uncovered through the detailed scrutiny that a 'small data' approach to Twitter, in supplement to some obvious virtues of Big Data approaches, is particularly well placed to provide.

Conceptualizing Big Data: Analysis of Case Studies

“…Moreover, the case studies pointed out additional aspects that need to be addressed, such as data inconsistencies and poor data quality (O'Leary, 2013a;Halamka, 2014;Mathew et al, 2015). Several studies also reported concerns for potential security and/or privacy issues (Halamka, 2014;Martinez & Walton, 2014;Stephansen & Couldry, 2014;Bettencourt-Silva et al, 2015). Applying proper analytics to the vast amounts of data is the key in gaining value and insights.…”

"Toward an architectural theory of innovation: Explicating design, networks, and microprocesses"

“…This paper is available at: http://www.journalcbi.co m/architectural-theoryof-innovationexplicating-designnetworks-andmicroprocesses.html mounting scholarly concern that particular microprocesses are not well understood (Fligstein & McAdam, 2012;Lok & Rond, 2013;McPherson & Sauder, 2013;Stephansen & Couldry, 2014).…”

Situated Social Media Use

“…Big data approaches to social media uses hold great promise, although they have been criticized for resting on a 'mythology' that more data is always better and leads to new knowledge and higher accuracy [2]. This has provoked some researchers to define their work as "small data" studies [14], where the focus is on smaller sets of data from social media, often in conjunction with interviews or some form of qualitative content or linguistic analysis.…”