AIMC Topic: Social Media

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Comparison of quality, empathy and readability of physician responses versus chatbot responses to common cerebrovascular neurosurgical questions on a social media platform.

Clinical neurology and neurosurgery
BACKGROUND: Social media platforms are utilized by patients prior to scheduling formal consultations and also serve as a means of pursuing second opinions. Cerebrovascular pathologies require regular surveillance and specialized care. In recent years...

Perception and sentiment analysis of palliative care in Chinese social media: Qualitative studies based on machine learning.

Social science & medicine (1982)
BACKGROUND: Traditional Chinese culture makes death a sensitive and taboo topic, leading patients and family members to refuse to choose palliative care.

Exploring mental health literacy on twitter: A machine learning approach.

Journal of affective disorders
OBJECTIVES: This study investigates whether reducing mental illness stigma, enhancing help-seeking efficacy, and maintaining positive mental health mediate the relationship between the recognition of mental disorders and help-seeking attitudes.

Hy-DeFake: Hypergraph neural networks for detecting fake news in online social networks.

Neural networks : the official journal of the International Neural Network Society
Nowadays social media is the primary platform for people to obtain news and share information. Combating online fake news has become an urgent task to reduce the damage it causes to society. Existing methods typically improve their fake news detectio...

Beyond the Posts: Analyzing Breast Implant Illness Discourse With Natural Language Processing and Deep Learning.

Aesthetic surgery journal
BACKGROUND: Breast implant illness (BII) is a spectrum of symptoms some people attribute to breast implants. Although causality remains unproven, patient interest has grown significantly. Understanding patient perceptions of BII on social media is cr...

Enhancing Marathon Enthusiast Engagement Through AI: A Quantitative Study on the Role of Social Media in Sports Communication.

Brain and behavior
PURPOSE: This study explores the impact of AI-driven personalization, interactive features, and real-time feedback on user engagement and experience among marathon enthusiasts.

Medical Mistrust in Online Cancer Communities: A Large-Scale Analysis Across 10 Cancer Entities.

Psycho-oncology
BACKGROUND: Medical mistrust is a barrier to optimal cancer care. Analyzing social media posts where patients voice mistrust provides an opportunity to understand its variations and derive potential ways to address medical mistrust.

Suicide ideation detection based on documents dimensionality expansion.

Computers in biology and medicine
Accurate and secure classifying informal documents related to mental disorders is challenging due to factors such as informal language, noisy data, cultural differences, personal information and mixed emotions. Conventional deep learning models often...

A novel framework for seasonal affective disorder detection: Comprehensive machine learning analysis using multimodal social media data and SMOTE.

Acta psychologica
Seasonal Affective Disorder (SAD) is a mood disorder characterized by recurring depressive episodes during specific seasons, particularly in Fall and Winter. With the rise of social media as a platform for self-expression, user-generated content offe...

The need for research on AI-driven social media and adolescent mental health.

Asian journal of psychiatry
The increasing integration of artificial intelligence (AI) in social media platforms has transformed digital interactions, particularly among adolescents. AI-driven algorithms curate highly personalized content, reinforcing behavioral patterns and op...