When the Feed Feels Personal: Emotional Dependency on Social Media Algorithms

Abstract

DOI : https://doi.org/10.82471/qem0g-t6g81

This paper explores the emotional dependence on algorithmic feeds in the everyday social media use. Using qualitative data from a phenomenological study of internet users in Kerala, this research analyses how users experience and make sense of algorithmic recommendations in their everyday emotional contexts. The study goes beyond the usual questions on algorithmic awareness or technical understanding. It looks at how individual feeds become relevant through moods, rituals, vulnerabilities and everyday interpretations. It implies that users’ interactions with algorithms are not only shaped by visibility but also by affective experiences. The research claims that emotional dependence on algorithms is not an issue of overuse, but rather a negotiated interaction between algorithmic personalisation and user affective interpretations, foregrounding user narratives.

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