TY  - JOUR
PY  - 2023//
TI  - Automatic detection of intimate partner violence victims from social media for proactive delivery of support
JO  - AMIA Joint Summits on Translational Science proceedings
A1  - Guo, Yuting
A1  - Kim, Sangmi
A1  - Warren, Elise
A1  - Yang, Yuan-Chi
A1  - Lakamana, Sahithi
A1  - Sarker, Abeed
SP  - 254
EP  - 260
VL  - 2023
IS  - 
N2  - 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
LA  - en
SN  - 2153-4063
UR  - http://dx.doi.org/
ID  - ref1
ER  -