arXiv:2608. 05183v1 Announce Type: cross Abstract: This dissertation analysed and discussed the differences in linguistic characteristics between pre-mortem and post-mortem social media content, and reported machine learning (ML) classifiers that achieved high performance in automatically detecting deaths of social networking site users from posts associated with their profiles.
By Nuhu Ibrahim, Riza Batista-Navarro
arXiv:2608. 15691v1 Announce Type: cross Abstract: Health misinformation circulating during pandemics can gain traction rapidly, creating harmful narratives that compete with public health guidance.
By Mkululi Sikosana, Sean Maudsley-Barton, Oluwaseun Ajao
The paper reviews how large language models are applied in mental health, covering areas such as social media analysis, clinical conversational agents, therapy support tools, prompt engineering, and multimodal learning. It synthesizes interdisciplinary studies that use social media posts, electronic medical records, and multimodal inputs to detect depression, assess suicide risk, provide personalized therapy, and generate psychoeducational content. The review also discusses advances in model interpretability, annotation strategies, multimodal fusion techniques, and highlights ethical, sociotechnical, and regulatory challenges while proposing frameworks for safe, equitable, and accountable deployment.
By Yisong Chen, Yifan Gao, Sijing Yu, Chuqing Zhao, Yang Lu
arXiv:2312. 04603v1 Announce Type: cross Abstract: Online polarization has attracted the attention of researchers for many years.
By Celina Treuillier (UL, CNRS, LORIA), Sylvain Castagnos (UL, CNRS, LORIA), Armelle Brun (UL, CNRS, LORIA)
arXiv:2510. 18908v2 Announce Type: replace-cross Abstract: Social media platforms such as Twitter (now X) provide rich data for analyzing public discourse, especially during crises such as the COVID-19 pandemic.
By Wangjiaxuan Xin, Shuhua Yin, Shi Chen, Yaorong Ge
arXiv:2608.29010v1 Announce Type: cross
Abstract: People share mental health diagnoses on social media, yet how such language becomes visible around their self-disclosure, and whether community engag...
By Renkai Ma, Lingyao Li, Shanting Chen, Chen Chen, Fan Yang, Yuanyuan Lei