Research with User-Generated Book Review Data: Legal and Ethical Pitfalls and Contextualized Mitigations.

iConference (1)(2023)

Cited 0|Views9
No score
The growing quantity of user-generated book reviews has opened up unprecedented opportunities for empirical research on books, reading, and readership. While there is an abundance of literature addressing the legal and ethical use of user-generated and social media data in general, for user-generated book reviews, such discussions have been mostly absent. From a library and information sciences perspective, user-generated book reviews can pose novel challenges because each book reviewer may simultaneously be (1) a presumably anonymous and safe online user; and, (2) an identifiable reader who can suffer real harm, e.g., cyber doxing and personal attack. This user/reader duality can create conflicting recommendations regarding which legal or ethical guidelines to follow. According to our review, potential legal issues include copyright infringement and violations of terms of service/end-user license agreements and privacy rights, while ethical concerns are centered on users’ expectations, informed consent, and institutional reviews. This paper reviews (1) potential legal and ethical pitfalls in leveraging user-generated book reviews; and, (2) professional and scholarly references that might serve as useful guidelines to avoid or manage these pitfalls.
Translated text
Key words
book review data,book review,research,user-generated
AI Read Science
Must-Reading Tree
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined