Why Social Media Users Press 'Not Interested': Motivations, Anticipated Effects, and Result Interpretation

Jihyeong Hong, Eun-Young Ko, Juho Kim, Jeong-woo Jang

Abstract: Social media users employ a variety of methods to avoid unwanted content in their personalized feeds. Platforms like Instagram and YouTube offer the ''Not Interested'' feature, allowing users to signal their preference to see less of certain content or similar types. Despite its wide availability on social media platforms, the ''Not Interested'' feature has received little academic attention, leaving a gap in understanding how it is perceived, used, and interpreted. This study investigates (1) the types of content users mark as ''Not Interested'', (2) their expectations about its effects, and (3) how they interpret its outcome. We conducted semi-structured interviews with 28 Instagram users who had used the ''Not Interested'' button more than 12 times over the past year, focusing on their experiences with this feature. Users used the ''Not Interested'' feature to avoid different types of content, ranging from problematic and personally discomforting to unrewarding. ''Not Interested'' feedback was considered unique in that it would remove similar content from their feeds without harming the creator. Users had mixed expectations about whose feed they wished their feedback to have an impact on. After submitting the feedback and observing the changes in the personalized feed, they were often uncertain of how each of their interactions was reflected in the algorithm. We discuss user characteristics that social media platforms need to consider, including diverse motivations related to content avoidance, users' demands to influence a broad range of content curation, and the need for granular control and deeper understanding of personalized algorithms.

External IDs:doi:10.1145/3757706