Social media sites continue to play a very important role in the lives of global society today. The simple and perceptively straightforward interfaces of the most frequently used social media applications are based on advanced algorithmic structures created to harvest behavioral information and optimize user engagement behavioral patterns conceptualized through the perspective of the so-called surveillance capitalism. Despite the fact that former studies have investigated the awareness of algorithmic systems among users and resistance tactics, there have been limited studies in analyzing how users form an intricate affective connection to algorithmic control. This qualitative research aims at filling this gap by investigating the paradoxical nature of user–algorithm relationships through semi-structured interviews with seventeen active social media users from five countries across three continents, purposely selected to represent a range of demographic and cultural backgrounds. Based on thematic analysis, the study establishes trends of what we call algorithmic ambivalence—simultaneous attraction to and resistance against algorithmic control on behalf of users—and the degree of awareness, affective responses, compulsive behavior, resistance strategies, and algorithmic bias perceptions. Three key theoretical results can be identified in this analysis: (1) a Spectrum of Algorithmic Ambivalence framework that explains the paradoxical nature of relations between users and algorithmic systems, (2) a more detailed typology of resistance practices categorized according to cultural and platform conditions, and (3) a framework of Agency of Algorithms that helps understand how surveillance capitalism constructs and consumes the complex emotional landscape and at the same time generates new forms of digital inequality.
Yuheng Jiang (Mon,) studied this question.
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