A systematic review of ethics disclosures in predictive mental health research
Applied machine learning (ML) has not yet coalesced on standard practices for research
ethics. For ML that predicts mental illness using social media data, ambiguous ethical …
ethics. For ML that predicts mental illness using social media data, ambiguous ethical …
Mental health analysis in social media posts: a survey
M Garg - Archives of Computational Methods in Engineering, 2023 - Springer
The surge in internet use to express personal thoughts and beliefs makes it increasingly
feasible for the social NLP research community to find and validate associations between …
feasible for the social NLP research community to find and validate associations between …
Detecting and understanding harmful memes: A survey
The automatic identification of harmful content online is of major concern for social media
platforms, policymakers, and society. Researchers have studied textual, visual, and audio …
platforms, policymakers, and society. Researchers have studied textual, visual, and audio …
A survey on pragmatic processing techniques
Pragmatics, situated in the domains of linguistics and computational linguistics, explores the
influence of context on language interpretation, extending beyond the literal meaning of …
influence of context on language interpretation, extending beyond the literal meaning of …
Systemization of Knowledge (SoK): Creating a Research Agenda for Human-Centered Real-Time Risk Detection on Social Media Platforms
Accurate real-time risk identification is vital to protecting social media users from online
harm, which has driven research towards advancements in machine learning (ML). While …
harm, which has driven research towards advancements in machine learning (ML). While …
Incorporating historical information by disentangling hidden representations for mental health surveillance on social media
The growing need to identify mental health conditions has paved the way for automated
computational methods for mental health surveillance on social media. However, inferring …
computational methods for mental health surveillance on social media. However, inferring …
CoSyn: Detecting implicit hate speech in online conversations using a context synergized hyperbolic network
The tremendous growth of social media users interacting in online conversations has led to
significant growth in hate speech, affecting people from various demographics. Most of the …
significant growth in hate speech, affecting people from various demographics. Most of the …
A human-centered approach to improving adolescent real-time online risk detection algorithms
A Alsoubai - Extended Abstracts of the 2023 CHI Conference on …, 2023 - dl.acm.org
Computational approaches to detect the online risks that the youth encounter have
presented promising potentials to protect them online. However, a major identified trend …
presented promising potentials to protect them online. However, a major identified trend …
Suicidal intention detection in tweets using BERT-based transformers
G Ananthakrishnan, AK Jayaraman… - 2022 International …, 2022 - ieeexplore.ieee.org
Suicidal intention or ideation detection is one of the evolving research fields in social media.
People use this platform to share their thoughts, tendencies, opinions, and feelings toward …
People use this platform to share their thoughts, tendencies, opinions, and feelings toward …
[PDF][PDF] ConversationMoC: Encoding Conversational Dynamics using Multiplex Network for Identifying Moment of Change in Mood and Mental Health Classification.
Understanding mental health conversation dynamics is crucial, yet prior studies often
overlooked the intricate interplay of social interactions. This paper introduces a unique …
overlooked the intricate interplay of social interactions. This paper introduces a unique …