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Linguistic analysis of online domestic violence testimonies in the context of COVID-19
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  • Valentin Buchner,
  • Sharina Hamm,
  • Barbara Medenica,
  • Marc L. Molendijk
Valentin Buchner
Leiden University Department of Clinical Psychology

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Sharina Hamm
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Barbara Medenica
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Marc L. Molendijk
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Worldwide, an increase in cases and severity of domestic violence (DV) has been reported as a result of the 2019 Coronavirus Disease (COVID-19) pandemic. As one’s language can provide insight in one’s mental health, this study analyzed word use in a DV online support group, aiming to investigate the impact of the COVID-19 pandemic on DV victims. Words reflecting social support and leisure activities were investigated as protective factors against linguistic indicators of depression. 5856 posts were collected from the r/domesticviolence subreddit and two neutral comparison subreddits (r/changemyview & r/femalefashionadvice). In the DV support group, the average number of daily posts increased significantly by 22% from pre-pandemic to mid-pandemic. Confirmatory analysis was conducted following a registered pre-analysis plan. DV victims used significantly more linguistic indicators of depression than individuals in the comparison groups. These linguistic indicators did not change with the onset of COVID-19. The use of negative emotion words was negatively related to the use of social support words (Spearman’s rho correlation coefficient [rho] = -.110) and words referring to leisure activities (rho = -.137). Pre-occupation with COVID-19 was associated with the use of negative emotion words (rho = .148).We conclude that language of DV victims is characterized by indicators of depression and this characteristic is stable over time. Concerns with COVID-19 could contribute to negative emotions, whereas social support and leisure activities could function to some degree as protective factors. A potential weakness of this study could be the limited ability of word count methods to assess the impact of stressors such as COVID-19. Future studies could make use of natural language processing and other advanced methods of linguistic analysis to learn about the mental health of DV victims.
Jan 2023Published in SAGE Open volume 13 issue 1 on pages 215824402211461. 10.1177/21582440221146135