Analyzing Reddit Stories of Sexual Violence: Incidents, Effects, and Requests for Advice
DOI:
https://doi.org/10.1609/icwsm.v19i1.35832Abstract
Warning: This paper may contain triggering language for some readers, especially survivors of sexual violence. Survivors of sexual violence sometimes share their experiences on social media, revealing their feelings and emotions and seeking advice. On platforms such as Reddit, some stories can be long---up to 40,000 characters. We posit that such long stories are demanding for helpers to read and respond to. Prior research has indicated that parts of these stories describing the incident, the effects on the poster, and advice requested by the poster are important. Highlighting those parts can draw helpers' attention toward key information and assist them in reading and responding to long stories. We first examine the stories posted on Reddit for the prevalence of these parts. Second, we develop a computational model to highlight these parts of a story. On ten-fold cross-validation of a dataset, our model achieves a macro F1 score of 0.82. In addition, we contribute METHREE, a dataset comprising 8,947 labeled sentences for these parts from Reddit stories. A survey of users who are helpers on some relevant subreddits shows that the parts highlighted by our tool represent important information and assist them while reading and responding to long stories. We find that these tool-generated highlights statistically significantly reduce the demandingness of long stories. Moreover, almost all helpers felt that highlighted stories are helpful and easier to read, understand, and respond to than nonhighlighted ones. In particular, on a 4-point Likert scale, there is about 0.7 point reduction in demandingess when stories were presented with highlights.Downloads
Published
2025-06-07
How to Cite
Garg, V., Javidi, H., Yuan, J., Xi, R., & Singh, M. P. (2025). Analyzing Reddit Stories of Sexual Violence: Incidents, Effects, and Requests for Advice. Proceedings of the International AAAI Conference on Web and Social Media, 19(1), 568–585. https://doi.org/10.1609/icwsm.v19i1.35832
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