ETHICS OF RESEARCH USING DIGITAL TRACE DATA: A Computational Social Science Perspective

Abstract

Although the invention of the web and social media has provided new opportunities for unobtrusive social research, ethical frameworks and regulations have been slow to adapt to changes in technology—leaving some ethical considerations open to interpretation by both researchers and ethics committees. Furthermore, traditional approaches to social science research ethics are better suited to ‘top-down’ research designs (e.g., surveys)—since primary data collections are prone to participant reactivity—whereas digital trace data research designs are based upon the use of secondary data, tend to be unobtrusive, ‘bottom-up’ and case-by-case. We contend that ethical clearance frameworks for research using digital trace data should be responsive, prospective to the use of secondary data, and common across institutions. While we highlight the distinct approach to ethics in digital trace data research, we emphasise that the usual considerations for human research ethics still apply: (a) informed consent, (b) distinction between private and public individuals, (c) confidentiality, and (d) cultural considerations.