[HTML][HTML] Review of Machine Learning solutions for Eating Disorders

S Ghosh, P Burger, M Simeunovic, J Maas… - International Journal of …, 2024 - Elsevier
Abstract Background Eating Disorders (EDs) are one of the most complex psychiatric
disorders, with significant impairment of psychological and physical health, and …

EDNet: Attention-Based Multimodal Representation for Classification of Twitter Users Related to Eating Disorders

M Abuhassan, T Anwar, C Liu, HK Jarman… - Proceedings of the …, 2023 - dl.acm.org
Social media platforms provide rich data sources in several domains. In mental health,
individuals experiencing an Eating Disorder (ED) are often hesitant to seek help through …

Unveiling the" Toxic" World of# Meanspo: Understanding Users' Emerging Online Eating Disorder Practices in X/Twitter

FF Nova, R Pfafman, C Logan Delaney… - Proceedings of the ACM …, 2024 - dl.acm.org
Meanspo, an antagonistic form of online support within the eating disorder (ED) community,
involves the direct solicitation or sharing of aggressive and insulting online content. This …

Does so-called “healthy” content on Instagram display balanced recipes? A pilot study in relation with the risk of unhealthy eating patterns in social network users.

G Del Pozo, P Ezan, M Moubassat, P Déchelotte - Appetite, 2024 - Elsevier
Objective social networks (SN) including Instagram have increased in popularity. However,
SN-mediated content may influence eating behaviors in a negative way. This study analyzed …

Neurofeedback on twitter: Evaluation of the scientific credibility and communication about the technique

SE Kober, F Buchrieser, G Wood - Heliyon, 2023 - cell.com
Neurofeedback is a popular technique to induce neuroplasticity with a controversial
reputation. The public discourse on neurofeedback, as a therapeutic and …

Explainable AI for Mental Disorder Detection via Social Media: A survey and outlook

Y Ibrahimov, T Anwar, T Yuan - arXiv preprint arXiv:2406.05984, 2024 - arxiv.org
Mental health constitutes a complex and pervasive global challenge, affecting millions of
lives and often leading to severe consequences. In this paper, we conduct a thorough …

Breaking the silence: leveraging social interaction data to identify high-risk suicide users online using network analysis and machine learning

D Lekkas, NC Jacobson - Scientific Reports, 2024 - nature.com
Suicidal thought and behavior (STB) is highly stigmatized and taboo. Prone to censorship,
yet pervasive online, STB risk detection may be improved through development of uniquely …

Figurative Health-mention Classification from Social Media using Graph Convolutional Networks

CS Krishna, VS Anoop - 2023 9th International Conference on …, 2023 - ieeexplore.ieee.org
The recent advancements in information and communication technologies paved the way for
the widespread availability and use of social media networks. People use social media …

Smartening Up the Home: User Perceptions and Experiences with Intelligent Personal Assistants for Lighting and Temperature Control

N Sharp, G Chinazzo, ZR Prajapati - Available at SSRN 4384366 - papers.ssrn.com
With the emergence of smart home assistant systems, artificial intelligence is increasingly
becoming integrated with people's lives at home. This study aimed to explore users' …

Optimizing Slogan Classification in Ubiquitous Learning Environment: A Hierarchical Multilabel Approach with Fuzzy Neural Networks

PN Ahmad, Y Liu, AM Shah, KY Lee… - Available at SSRN … - papers.ssrn.com
Recent advances in social media analytics research have delved into the intricate realm of
slogans and endorsements of products or services, posing classification challenges in …