A Thematic Analysis of the Experience of Fear of Judgment Among Digital Content Creators in Cyberspace
Keywords:
Fear of judgment, content creators, cyberspace, thematic analysis, online self-presentation, social evaluative anxietyAbstract
This study aimed to conduct a thematic analysis of the experience of fear of judgment among digital content creators. This qualitative study used a thematic analysis design. The participants were 22 digital content creators living in Tehran, selected through purposive sampling based on at least one year of regular content production experience on social media platforms. Data were collected through in-depth semi-structured interviews, and sampling continued until theoretical saturation was reached. Interviews lasted between 45 and 80 minutes. All interviews were audio-recorded after informed consent, transcribed verbatim, and prepared for analysis. Data were analyzed using NVivo software and Braun and Clarke’s six-phase thematic analysis framework. To enhance trustworthiness, member checking, peer review, analytic memo writing, and an audit trail were used. The analysis generated five main themes: pre-publication anxiety, sensitivity to negative feedback and audience silence, self-censorship and image management, emotional exhaustion caused by continuous visibility, and coping strategies for rebuilding psychological safety. The findings indicated that fear of judgment among content creators is not merely a reaction to direct criticism. Rather, it is experienced through anticipated evaluation, comparison with other creators, concerns about reputation loss, dependence on numerical metrics, and ongoing doubts about personal authenticity. Fear of judgment among digital content creators is a multilayered phenomenon shaped by social evaluative anxiety, platform algorithms, visibility pressure, and the attention economy. Reducing this fear requires individual, educational, and platform-level interventions that strengthen emotion regulation, digital boundary-setting, and safer online environments with less dependence on judgment-based metrics.
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