Creepy, Invasive, and Exploitative Algorithms: A CPM Analysis of Users’ Privacy Breakdowns and Recalibration Practices with Social Media Algorithms
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’ (N=636) 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.
Matthew J. A. Craig
Assistant Professor of Computer-Mediated Communication
Matthew Craig is an Assistant Professor of Computer-Mediated Communication in the School of Communication, Journalism, and Media at Central Michigan University (CMU) and lab faculty with the Communication and Social Robotics Labs (COMBOTLABS). Before CMU, Matthew was the inaugural College of Communication and Information Postdoctoral Research Associate in the Information Integrity Institute at Tennessee’s flagship university, the University of Tennessee, Knoxville (Dr. Catherine Luther, Faculty Mentor). Matthew’s research interests are in human-machine communication and new media, focusing on the intersections of human-machine communication, privacy management, and society.