Hashtag campaigns calling out sexual violence and rape myths offer a unique context for disclosing sexual victimization on social media. This study investigates the applicability of adaptive self-reflection as a potential self-effect from such public disclosures of unreported sexual victimization experiences by analyzing 92,583 tweets that invoked #WhyIDidntReport. A supervised machine learning classifier determined that 61.8% of the tweets were self-disclosures of sexual victimization. Linguistic Inquiry and Word Count (LIWC) analysis showed statistically significant differences in four psycholinguistic dimensions (greater use of past focus, cognitive processes, insight, and causation words) connected with reflective processing in tweets with self-disclosed sexual victimization compared to those without. Additionally, topic modeling and thematic analysis identified nine salient topics within the self-disclosing tweets, comprising three self-distanced representations (i.e., relatively abstract and insightful construals) of the unwanted experiences: (a) acknowledging one’s previously unacknowledged victimization, (b) reaffirming one’s rationale for not reporting, and (c) decrying invalidating response to one’s disclosure. Moving beyond reception effects and social support in extant research about social media as a coping tool, this study provides new empirical insights into the potential of social media to promote expressive meaning-making of upsetting and traumatic experiences in ways that support recovery and resilience.

中文翻译：

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作为社交媒体自我效应的适应性自我反思：标签活动中未报告性受害自我披露的计算文本分析的见解


呼吁性暴力和强奸神话的标签活动为在社交媒体上披露性受害行为提供了独特的背景。本研究通过分析 92,583 条调用 #WhyIDidntReport 的推文，调查了适应性自我反思的适用性，作为公开披露未报告的性受害经历的潜在自我效应。监督机器学习分类器确定 61.8% 的推文是性受害的自我披露。语言查询和字数（LIWC）分析显示，与那些没有自我披露性受害的推文相比，在与反思处理相关的四个心理语言学维度（更多地使用过去的焦点、认知过程、洞察力和因果词）方面存在统计显着差异。此外，主题建模和主题分析确定了自我披露推文中的九个显着主题，包括对不良经历的三种自我疏远表示（即相对抽象和有洞察力的解释）：（a）承认自己以前未承认的受害行为，（b）重申不报告的理由，以及 (c) 谴责对其披露的回应无效。这项研究超越了现有关于社交媒体作为应对工具的研究中的接受效应和社会支持，为社交媒体的潜力提供了新的实证见解，以支持恢复和复原力的方式促进令人沮丧和创伤经历的表达意义建构。