A Mixed-Methods Approach to Ethical Data Extraction in Social Media Studies

Publication: Chapter in book/Conference proceedingChapter in edited volume


Across social media platforms users (sub)consciously represent themselves in a way that is appropriate for their intended audience. This has unknown impacts on studies with unobtrusive designs based on digital (social) platforms, and studies of contemporary social phenomena in online settings. A lack of appropriate methods to identify, control for, and mitigate the effects of self-representation, the propensity to express socially responding characteristics or self-censorship in digital settings, hinders the ability of researchers to confidently interpret and generalize their findings. This article discusses a methodological approach to fill this research gap. A case study of paid Amazon Mechanical Turk respondents (n = 509) is presented where respondents completed psychometric surveys and provided fully anonymized access to their Facebook timelines. This case study concentrates on data collection and anonymization processes, and discusses issues in data harvested over the Internet.
Original languageEnglish
Title of host publicationSAGE Research Methods Cases Part 2
Publication statusPublished - 2018

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102

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