@article{ref1,
title="Automatic detection of intimate partner violence victims from social media for proactive delivery of support",
journal="AMIA Joint Summits on Translational Science proceedings",
year="2023",
author="Guo, Yuting and Kim, Sangmi and Warren, Elise and Yang, Yuan-Chi and Lakamana, Sahithi and Sarker, Abeed",
volume="2023",
number="",
pages="254-260",
abstract="Social media platforms are increasingly being used by intimate partner violence (IPV) victims to share experiences and seek support. If such information is automatically curated, it may be possible to conduct social media based surveillance and even design interventions over such platforms. In this paper, we describe the development of a supervised classification system that automatically characterizes IPV-related posts on the social network Reddit. We collected data from four IPV-related subreddits and manually annotated the data to indicate whether a post is a self-report of IPV or not. Using the annotated data (N=289), we trained, evaluated, and compared supervised machine learning systems. A transformer-based classifier, RoBERTa, obtained the best classification performance with overall accuracy of 78% and IPV-self-report class",
language="en",
issn="2153-4063",
doi="",
url="http://dx.doi.org/"
}