Rape narratives analysis through natural language processing: Survivor self-label, narrative time span, faith, and rape terminology.

Abstract

Rape-survivor identity is a sign of recovery and positive therapeutic progress among rape victims. This study is one of the few to focus on factors predicting self-labeling as a survivor among self-acknowledged rape victims by evaluating the contribution of the time span of the rape narrative, rape terminology, and expression of faith. Method: The data were elicited from 3,794 rape narratives published on Brave Miss World, a website established, inter alia, to allow rape victims to share their stories. To identify the key concepts within rape narratives, we performed text mining based on natural language processing (NLP) and developed a model. Structural equation modeling (SEM) was used to test the model's goodness-of-fit analysis. Results: The results indicated a good fit between the theoretical model and the data. Time predicted expressions of faith and the use of rape terminology, and there was a positive correlation between faith and the use of rape terminology. Both expressions of faith and the use of rape terminology mediated between time span and self-labeling as a survivor, with a significant positive effect on self-labeling as a survivor. Conclusions: The results suggest that addressing rapevictim faith and the use of rape terminology in the depiction of their sexual trauma may be beneficial for the therapeutic process and postrape recovery. Clinical Impact StatementThis research suggests that practitioners working with victims of sexual victimization should address victims' postrape spiritual state and development. Also, this study highlights the importance of the terminology used by victims of rape and sexual assault when describing their traumatic experiences.

Breaking the silence: A qualitative analysis of trauma narratives submitted online by first responders.

“…Although it is well known that treatment-seeking can be discouraged, inhibited, and barriered for highly trauma exposed populations, especially first responders, there are few examinations of trauma narration conducted outside of formal treatment. Of the studies that exist, a small number have examined the online media content (i.e., YouTube videos, blogs, forums, or threads) of individuals recovering from trauma, including victims of sexual assault or rape (Fawcett & Shrestha, 2016; Levy & Eckhaus, 2020; Moors & Webber, 2013), burn survivors (Badger et al, 2011); women with traumatic birth experiences (Blainey & Slade, 2015); and persons who experienced multiple traumas or were diagnosed with PTSD (Cohn et al, 2004; Ramanathan, 2015; Salzmann-Erikson & Hiçdurmaz, 2017). Generally, these studies focused on the logistics of the narratives, such as the structure and format of narration and online interactions, and the content, such as that writers share information about their reasons for writing their stories, their symptomology, how their symptoms restrict their daily lives, and how they cope.…”

A qualitative exploration of women's resilience in the face of homelessness

“…Though researchers have positioned women as survivors, particularly with regard to domestic violence (Clark et al, 2019;Kahan et al, 2020;Klopper et al, 2014;Kunkel & Guthrie, 2016;Ragavan et al, 2016), the women in this study understood themselves as survivors. This was a critical psychological position (Levy & Eckhaus, 2020) that enabled them to transition from a sense of hopelessness to being hopeful for the future. The key enabling condition that facilitated this positioning was connection and relatedness with individuals that the women found more helpful when working with social and housing services.…”

Exploring Negative Spillover Effects on Stakeholders: A Case Study on Social Media Talk about Crisis in the Food Industry Using Data Mining

“…For analysis of the data, we used natural language processing (NLP) by employing a combination of n-gram frequencies and bag-of-words (BoW) techniques. This combination was employed in order to identify latent themes and develop variables for statistical purposes [26].…”