Perspective: Acknowledging Data Work in the Social Media Research Lifecycle

Abstract

This perspective article suggests considering the everyday research data management work required to accomplish social media research along different phases in a data lifecycle to inform the ongoing discussion of social media research data’s quality and validity. Our perspective is informed by practical experience of archiving social media data, by results from a series of qualitative interviews with social media researchers, as well as by recent literature in the field. We emphasize how social media researchers are entangled in complexities between social media platform providers, social media users, other actors, as well as legal and ethical frameworks, that all affect their everyday research practices. Research design decisions are made iteratively at different stages, involving many decisions that may potentially impact the quality of research. We show that these decisions are often hidden, but that making them visible allows us to better understand what drives social media research into specific directions. Consequently, we argue that untangling and documenting choices during the research lifecycle, especially when researchers pursue specific approaches and may have actively decided against others (often due to external factors) is necessary and will help to spot and address structural challenges in the social media research ecosystem that go beyond critiques of individual opportunistic approaches to easily accessible data.

From theory to practice: insights and hurdles in collecting social media data for social science research

“…John and Nissenbaum ( 2019 ) wrote that “researchers are ultimately dependent on tech companies for data and have to find a way to collaborate while serving the public interest and avoiding bias” (p. 3). The increased restrictions in APIs leave social media researchers grappling with non-public, legally ambiguous, and ethically gray approaches to collecting data, or push them toward impermanent types of data that hamper the detection of trends (Weller and Kinder-Kurlanda, 2015 ; Kinder-Kurlanda and Weller, 2020 ). Business-oriented users of data continue unencumbered, while access to data for public good is curtailed (Bruns, 2019 ; John and Nissenbaum, 2019 ; Acker and Kreisberg, 2020 ).…”