Methods for Generating Typologies of Non/use
Abstract
Proceedings of the ACM on Human-Computer Interaction
Prior studies of technology non-use demonstrate the need for approaches that go beyond a simple binary distinction between users and non-users. This paper proposes a set of two different methods by which researchers can identify types of non/use relevant to the particular sociotechnical settings they are studying. These methods are demonstrated by applying them to survey data about Facebook non/use. The results demonstrate that the different methods proposed here identify fairly comparable types of non/use. They also illustrate how the two methods make different trade offs between the granularity of the resulting typology and the total sample size. The paper also demonstrates how the different typologies resulting from these methods can be used in predictive modeling, allowing for the two methods to corroborate or disconfirm results from one another. The discussion considers implications and applications of these methods, both for research on technology non/use and for studying social computing more broadly.
Document Type
Conference Proceeding
Publication Date
5-29-2020
Recommended Citation
Saxena, Devansh; Skeba, Patrick; Guha, Shion PhD; and Baumer, Eric P.S., "Methods for Generating Typologies of Non/use" (2020). Health Services and Informatics Research. 104.
https://researchrepository.parkviewhealth.org/informatics/104