Abstract
Social media content filtering algorithms can both provide desired personalized content and ads for users. However, sometimes these recommendations can resemble individual private information. How might users navigate these experiences to best manage their private information? The present exploratory study utilizes the rules- and systems-based framework of communication privacy management (CPM) theory to explore social media users’ experiences of privacy breakdowns with social media algorithms and investigates what users do in response to said breakdowns. These responses were refined using content analysis and divided into different categories of privacy breakdowns and recalibration strategies. Implications for future research surrounding human-machine communication privacy management are discussed in light of our findings.
DOI
10.30658/hmc.10.10
Author ORCID Identifier
Matthew J. A. Craig: 0000-0002-4824-566X 
Recommended Citation
Craig, M. J. A., & Child, J. T. (2025). Creepy, invasive, and exploitative algorithms: A CPM analysis of users’ privacy breakdowns and recalibration practices with social media algorithms. Human-Machine Communication, 10, 223–242. https://doi.org/10.30658/hmc.10.10
Included in
Communication Technology and New Media Commons, Graphics and Human Computer Interfaces Commons, Social Media Commons
Accessibility Statement
This item was created or digitized prior to April 24, 2027, or is a reproduction of legacy media created before that date. It is preserved in its original, unmodified state specifically for research, reference, or historical recordkeeping. In accordance with the ADA Title II Final Rule, the University Libraries provides accessible versions of archival materials upon request. To request an accommodation for this item, please submit an accessibility request form.
Submit Article
This journal supports Open Science Badges
