It’s not you, it’s me: A thematic analysis of written causal attributions for favorable and unfavorable feedback on different types of Instagram image sharing

Abstract

Previous research has provided valuable insights into how virtual likes and comments on self-presentational content affect users’ emotions and self-evaluations, yet less is known about the causal attributions people make in response to such feedback. This study analyzed responses to an open-ended question to explore the types of causal attributions individuals make for favorable and unfavorable feedback on different types of Instagram posts – selfies, elsies (self-images taken by others), and memes. Undergraduate participants (N = 125; 77% female; 81% 17- to 24-years-old) were randomly assigned to one of three image conditions (selfie, elsie, or meme) and told their selected image would be posted to a university-affiliated Instagram account. After a 5-minute distraction period, during which participants believed their image was posted for feedback, they were told they had received either favorable or unfavorable (fabricated) feedback. They were asked to write down the perceived causes of the feedback they received in an open-ended question. Additionally, participants reported their perception of societal attitudes toward selfies compared to elsies, to explore whether these perceptions may have influenced their attributions. Findings revealed that self-focused images (selfies and elsies) more frequently prompted internal attributions – especially appearance-related – compared to meme posts, which elicited primarily external attributions tied to audience reception. Despite recognizing society’s negative perceptions of selfie-posters, participants rarely attributed feedback to these broader social norms. The results suggest that posting self-images can heighten self-awareness and self-objectification, leading individuals to internalize social feedback. These attribution patterns carry implications for self-esteem and self-presentation. Understanding how users interpret feedback may inform efforts to promote healthier engagement with social media.