Towards an ethical framework for publishing Twitter data in social research: taking into account users’ views, online context and algorithmic estimation

Williams, Matthew L ORCID: https://orcid.org/0000-0003-2566-6063, Burnap, Pete ORCID: https://orcid.org/0000-0003-0396-633X and Sloan, Luke ORCID: https://orcid.org/0000-0002-9458-9332 2017. Towards an ethical framework for publishing Twitter data in social research: taking into account users’ views, online context and algorithmic estimation. Sociology 51 (6) , pp. 1149-1168. 10.1177/0038038517708140

Preview

PDF - Published Version Available under License Creative Commons Attribution. Download (590kB) | Preview

Abstract

New and emerging forms of data, including posts harvested from social media sites such as Twitter, have become part of the sociologist’s data diet. In particular, some researchers see an advantage in the perceived ‘public’ nature of Twitter posts, representing them in publications without seeking informed consent. While such practice may not be at odds with Twitter’s terms of service, we argue there is a need to interpret these through the lens of social science research methods, that imply a more reflexive ethical approach than provided in ‘legal’ accounts of the permissible use of these data in research publications. To challenge some existing practice in Twitter based research, this paper brings to the fore i) views of Twitter users through analysis of online survey data, ii) the effect of context collapse and online disinhibition on the behaviors of users, and iii) the publication of identifiable sensitive classifications derived from algorithms.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Social Sciences (Includes Criminology and Education) Computer Science & Informatics
Subjects:	H Social Sciences > H Social Sciences (General)
Uncontrolled Keywords:	algorithms, computational social science, social data science, context collapse, ethics, social media, twitter
Additional Information:	This article is distributed under the terms of the Creative Commons Attribution 3.0 License (http://www.creativecommons.org/licenses/by/3.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Publisher:	SAGE
ISSN:	0038-0385
Date of First Compliant Deposit:	5 April 2017
Date of Acceptance:	1 March 2017
Last Modified:	19 Aug 2024 12:36
URI:	https://orca.cardiff.ac.uk/id/eprint/99642

Citation Data

Cited 248 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item