Why do people resist algorithms? From the perspective of short video usage motivations

Algorithms embedded in media applications increasingly influence individuals' media practice and behavioral decisions. However, it is also important to consider how the influence of such algorithms can be resisted. Few studies have explored the resistant outcomes of the interactions with algorithms. Based on an affordance perspective, this study constructed a formation framework of algorithmic resistance in the context of short videos in China. Survey responses from 2,000 short video users to test the model. Exploratory factor analysis, confirmatory factor analysis, and structural equation modeling were used for data analysis. The findings reveal two types of "moderate" resistance: avoidance and obfuscation. Specific needs, such as the motivations of peeking and escapism, are significantly related to perceived algorithmic affordance, which, in turn, encourages the tactics of avoidant and obfuscated resistance. The results provide new insights into the potential formation mechanisms of algorithmic resistance. The forms of resistance highlighted in the paper evolve alongside algorithms and have significant practical implications for users and platforms.