숏폼 미디어 이용자 유형화에 대한 연구 : 알고리즘 수용도, 알고리즘 대응 행동, 알고리즘 리터러시를 중심으로

초록

This study classified user types in an algorithm-based short-form media environment and examined differences in psychological attitudes across these types. Specifically, user types were identified through K-means cluster analysis based on algorithm acceptance, algorithm literacy, active management behavior, and non-management behavior. Differences in algorithm-related perceptions and evaluations, as well as background variables, were then examined across the identified user groups. Based on data collected from 311 Chinese TikTok users, four distinct user types were identified: the “pragmatic acceptance type,” the “strategic utilization type,” the “low-acceptance avoidance type,” and the “low-awareness disengaged type.” Furthermore, statistically significant differences were found across user types in recommendation satisfaction, self-efficacy, and privacy concerns. The strategic utilization type generally showed the highest levels across these variables, whereas the low-acceptance avoidance type and the low-awareness disengaged type demonstrated relatively lower levels of self-efficacy and lower awareness. In addition, significant differences in background variables were observed across user types.

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