EASY DATA, USUAL SUSPECTS, SAME OLD PLACES? A SYSTEMATIC REVIEW OF METHODOLOGICAL APPROACHES IN DIGITAL ACTIVISM RESEARCH BETWEEN 1995-2019 - Ozkula, Suay Melisa; Reilly, Paul; Hayes, Jennifer (AoIR Selected Papers of Internet Research, 2020)
Burgess and Bruns (2015) have linked the computational turn in social media research to a rise in studies that focus exclusively on ‘easy’ data, such as the ‘low hanging fruit’ provided by Twitter hashtags. This paper set out to explore whether this preponderance of easy data and studies focused on the 2011-12 protests is evident in research between 1995 and 2019 through a systematic review of digital activism literature (N = 1444). A particular focus of the review was the extent to which digital activism research revolved around the use of computational digital methods, case studies based in Europe and North America and data gathered from single online platforms (e.g. Twitter). The review showed that most of these studies focused on social movements, campaigns, activists, and parties based in the United Kingdom and United States, and were conducted by researchers based in universities in these countries. In contrast, there were relatively few articles addressing activism, institutions and platforms in non-Western /Global South contexts with the exception of the Arab Spring in 2011. In terms of methodological approaches, traditional research methods and big data digital methods studies were prevalent. In response to the easy data hypothesis, the study found that Twitter was the most researched platform in the corpus, but that digital methods were not as commonly deployed in these articles as traditional methods. Thus, the paper concludes argues in favor of greater diversity in digital activism research in terms of its methods, participants, and countries of origin.