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Past studies of sexual assault have found that passive voice descriptions of rape elicit an increased perception of victim responsibility in readers. Building on this, we investigate rape survivors' self-perceptions and perspectives, as disclosed online, in relation to passive voice vs. active voice usage. From roughly 65,000 posts written by over 17,000 users on Reddit’s r/sexualassault board, we group texts into a passive voice group and an active voice group, respectively. We then use textual forma mentis networks, a cognitive network science approach, to create network representations from text such that nodes represent words/concepts while links represent syntactic and semantic relationships between them. These network representations make it possible to investigate the structural linguistic, cognitive, and emotional patterns that are prevalent in passive voice and active voice narratives, respectively. Ranking nodes by closeness centrality and comparing across networks, we identify nodes that are significantly more central to one network compared to the other, thus identifying characteristic concepts that semantically differentiate the two groups of narratives. We then investigate the contexts of these concepts through an in-depth semantic frame analysis. We find that concepts related to psychological distress (e.g. PTSD, flashback) are significantly more central to the passive voice network, providing quantitative evidence of a link between passive voice usage and an increased focus on psychological distress. We also find that family members (e.g. parent, brother) are more central to the active voice network, suggesting a connection between active voice usage and an increased focus on others' roles in rape survivors’ experiences. Our quantitative results have important implications for rape survivors as well as mental health professionals regarding the link between language and mental health.
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Stored only when both papers are in the corpus — 11 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.