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Sexual Harassment Story Classification and Key Information Identification

Published: 03 November 2019 Publication History

Abstract

Recently more and more personal stories about sexual harassment are shared online, mainly inspired by the \#MeToo movement. Safecity is an online forum for victims of sexual harassment to share their personal experience. Previous study applied neural network models to classify the harassment forms of the stories. To uncover patterns of sexual harassment, the extraction of the key elements and the categorization of these stories in different dimensions can be useful as well. In this study, we proposed neural network models to extract key elements including harasser, time, location and trigger words. In addition, we categorized these stories from different dimensions, such as location, time, and harassers' characteristics, including their age range, single/multiple harassers, profession, and relationship with the victims. We further demonstrated that encoding the key element information in the story categorization model can improve its performance. The proposed approaches and analysis would be helpful in automatically filing reports, raising public awareness, making preventing strategies and etc.

References

[1]
Sweta Agrawal and Amit Awekar. 2018. Deep Learning for Detecting Cyberbullying Across Multiple Social Media Platforms. CoRR, Vol. abs/1801.06482 (2018).
[2]
Sairam Balani and Munmun De Choudhury. 2015. Detecting and Characterizing Mental Health Related Self-Disclosure in Social Media. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems. 1373--1378.
[3]
Akshay Chaturvedi, Onkar Pandit, and Utpal Garain. 2018. CNN for Text-Based Multiple Choice Question Answering. In ACL. ACL, 272--277.
[4]
Arijit Ghosh Chowdhury, Ramit Sawhney, Puneet Mathur, Debanjan Mahata, and Rajiv Ratn Shah. 2019. Speak up, Fight Back! Detection of Social Media Disclosures of Sexual Harassment. In NAACL: Student Research Workshop. ACL.
[5]
Linda Lewis Griffith. 2018. Guilt, doubt, fear: Why women don't report sexual assault.
[6]
Sepp Hochreiter and Jürgen Schmidhuber. 1997. Long Short-Term Memory. Neural Computation, Vol. 9, 8 (1997), 1735--1780.
[7]
Sweta Karlekar and Mohit Bansal. 2018. SafeCity: Understanding Diverse Forms of Sexual Harassment Personal Stories. In EMNLP .
[8]
A. Khatua, E. Cambria, and A. Khatua. 2018. Sounds of Silence Breakers: Exploring Sexual Violence on Twitter. In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 397--400.
[9]
Yoon Kim. 2014. Convolutional Neural Networks for Sentence Classification. CoRR, Vol. abs/1408.5882 (2014). arxiv: 1408.5882 http://arxiv.org/abs/1408.5882
[10]
Suzanne Goodney Lea, Elsa D'Silva, and Abhijith Asok. 2017. Women's strategies addressing sexual harassment and assault on public buses: an analysis of crowdsourced data. Crime Prevention and Community Safety, Vol. 19, 3 (01 Sep 2017), 227--239. https://doi.org/10.1057/s41300-017-0028--1
[11]
Yann Lecun and Yoshua Bengio. 1995. Convolutional networks for images, speech, and time-series .
[12]
Tomas Mikolov, Martin Karafiát, Lukás Burget, Jan Cernocký, and Sanjeev Khudanpur. 2010. Recurrent neural network based language model. In INTERSPEECH .
[13]
Rachel E. Morgan and Jennifer L. Truman. 2018. Criminal Victimization, 2017 . Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.
[14]
Thien Huu Nguyen and Ralph Grishman. 2015. Event Detection and Domain Adaptation with Convolutional Neural Networks. In ACL .
[15]
Nicolas Schrading, Cecilia Ovesdotter Alm, Ray Ptucha, and Christopher Homan. 2015a. An Analysis of Domestic Abuse Discourse on Reddit. In EMNLP. 2577--2583.
[16]
Nicolas Schrading, Cecilia Ovesdotter Alm, Raymond Ptucha, and Christopher Homan. 2015b. #WhyIStayed, #WhyILeft: Microblogging to Make Sense of Domestic Abuse. In NAACL . Denver, Colorado, 1281--1286.
[17]
Mike Schuster, Kuldip K. Paliwal, and A. General. 1997. Bidirectional recurrent neural networks. IEEE Transactions on Signal Processing (1997).
[18]
Pengcheng Yang, Xu SUN, Wei Li, and Shuming Ma. 2018. Automatic Academic Paper Rating Based on Modularized Hierarchical Convolutional Neural Network. In ACL. ACL, 496--502.
[19]
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alexander J. Smola, and Eduard H. Hovy. 2016. Hierarchical Attention Networks for Document Classification. In HLT-NAACL .

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  • (2024)"Just Like, Risking Your Life Here": Participatory Design of User Interactions with Risk Detection AI to Prevent Online-to-Offline Harm Through Dating AppsProceedings of the ACM on Human-Computer Interaction10.1145/36869068:CSCW2(1-41)Online publication date: 8-Nov-2024
  • (2024)Support in Short Form: Investigating TikTok Comments on Videos with #HarassmentExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650849(1-8)Online publication date: 11-May-2024
  • (2024)Classification of domestic violence Persian textual content in social media based on topic modeling and ensemble learningHeliyon10.1016/j.heliyon.2024.e39953(e39953)Online publication date: Oct-2024
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  1. Sexual Harassment Story Classification and Key Information Identification

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    cover image ACM Conferences
    CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management
    November 2019
    3373 pages
    ISBN:9781450369763
    DOI:10.1145/3357384
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 03 November 2019

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    Author Tags

    1. sexual harassment
    2. sexual harassment extraction
    3. text classification

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    CIKM '19 Paper Acceptance Rate 202 of 1,031 submissions, 20%;
    Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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    View all
    • (2024)"Just Like, Risking Your Life Here": Participatory Design of User Interactions with Risk Detection AI to Prevent Online-to-Offline Harm Through Dating AppsProceedings of the ACM on Human-Computer Interaction10.1145/36869068:CSCW2(1-41)Online publication date: 8-Nov-2024
    • (2024)Support in Short Form: Investigating TikTok Comments on Videos with #HarassmentExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650849(1-8)Online publication date: 11-May-2024
    • (2024)Classification of domestic violence Persian textual content in social media based on topic modeling and ensemble learningHeliyon10.1016/j.heliyon.2024.e39953(e39953)Online publication date: Oct-2024
    • (2023)Identifying Common Barriers to Formal Disclosure of Sexual ViolenceHandbook of Research on Exploring Gender Equity, Diversity, and Inclusion Through an Intersectional Lens10.4018/978-1-6684-8412-8.ch019(397-422)Online publication date: 30-Jun-2023
    • (2023)Sliding into My DMs: Detecting Uncomfortable or Unsafe Sexual Risk Experiences within Instagram Direct Messages Grounded in the Perspective of YouthProceedings of the ACM on Human-Computer Interaction10.1145/35795227:CSCW1(1-29)Online publication date: 16-Apr-2023
    • (2023)A Systematic Literature Review of the Use of Computational Text Analysis Methods in Intimate Partner Violence ResearchJournal of Family Violence10.1007/s10896-023-00517-738:6(1205-1224)Online publication date: 21-Mar-2023
    • (2022)From 'Friends with Benefits' to 'Sextortion:' A Nuanced Investigation of Adolescents' Online Sexual Risk ExperiencesProceedings of the ACM on Human-Computer Interaction10.1145/35551366:CSCW2(1-32)Online publication date: 11-Nov-2022
    • (2021)A Human-Centered Systematic Literature Review of the Computational Approaches for Online Sexual Risk DetectionProceedings of the ACM on Human-Computer Interaction10.1145/34796095:CSCW2(1-38)Online publication date: 18-Oct-2021
    • (2021)Designing a Chatbot for Survivors of Sexual Violence: Exploratory Study for Hybrid Approach Combining Rule-based Chatbot and ML-based ChatbotProceedings of the Asian CHI Symposium 202110.1145/3429360.3468203(160-166)Online publication date: 8-May-2021

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