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Identifying informational norms in Mumsnet Talk: a reflexive-linguistic approach to internet research ethics

Mackenzie, Jai

Authors

Jai Mackenzie



Abstract

In recent years, researchers working within the discipline of applied linguistics and beyond have discovered stimulating opportunities to study human interaction, rituals and behaviours online. But with these opportunities come concerns for the human subjects ‘behind’ online data, most notably, their rights to privacy and freedom from harm. Applied linguists working with data from the internet therefore have a responsibility to continually scrutinise and re-evaluate the ethics of their research methods in line with fast-moving technological developments. In the past decade, an increasing number of scholars have advocated a case-based, context-sensitive approach to the issue of privacy, ethics and internet research. But the mechanisms for applying such an approach are often not made explicit, leaving researchers unsure how to proceed ethically in increasingly complex and shifting research contexts. Using a study of the Mumsnet Talk forum as a case, I show how my self-reflexive and linguistic approach, which draws on established traditions in qualitative research, has helped me to understand what many users of this forum see as normal information flows within this setting. I suggest that such a reflexive-linguistic approach is of value to internet researchers working within the applied linguistic discipline and beyond, who wish to make sensitive, informed ethical judgements that minimise the risk of harm to their participants.

Citation

Mackenzie, J. (2017). Identifying informational norms in Mumsnet Talk: a reflexive-linguistic approach to internet research ethics. Applied Linguistics Review, 8(2-3), 293-314. https://doi.org/10.1515/applirev-2016-1042

Journal Article Type Article
Acceptance Date Oct 20, 2016
Online Publication Date Nov 17, 2016
Publication Date Jun 1, 2017
Deposit Date Nov 9, 2018
Publicly Available Date Nov 9, 2018
Journal Applied Linguistics Review
Electronic ISSN 1868-6311
Publisher De Gruyter
Peer Reviewed Peer Reviewed
Volume 8
Issue 2-3
Pages 293-314
DOI https://doi.org/10.1515/applirev-2016-1042
Public URL https://nottingham-repository.worktribe.com/output/1238722
Publisher URL https://www.degruyter.com/view/j/alr.2017.8.issue-2-3/applirev-2016-1042/applirev-2016-1042.xml

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