AIMC Topic: Social Media

Clear Filters Showing 71 to 80 of 495 articles

Characteristics of ChatGPT users from Germany: Implications for the digital divide from web tracking data.

PloS one
A major challenge of our time is reducing disparities in access to and effective use of digital technologies, with recent discussions highlighting the role of AI in exacerbating the digital divide. We examine user characteristics that predict usage o...

Natural Language Processing and Social Determinants of Health in Mental Health Research: AI-Assisted Scoping Review.

JMIR mental health
BACKGROUND: The use of natural language processing (NLP) in mental health research is increasing, with a wide range of applications and datasets being investigated.

Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial.

Journal of medical Internet research
BACKGROUND: With increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment meth...

Hierarchical graph-based integration network for propaganda detection in textual news articles on social media.

Scientific reports
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda, serving as a vital source of self-reported symptoms related to Covid-19. Existing graph-based mode...

Efficacy and empathy of AI chatbots in answering frequently asked questions on oral oncology.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: Artificial intelligence chatbots have demonstrated feasibility and efficacy in improving health outcomes. In this study, responses from 5 different publicly available AI chatbots-Bing, GPT-3.5, GPT-4, Google Bard, and Claude-to frequently...

Public Health Discussions on Social Media: Evaluating Automated Sentiment Analysis Methods.

JMIR formative research
BACKGROUND: Sentiment analysis is one of the most widely used methods for mining and examining text. Social media researchers need guidance on choosing between manual and automated sentiment analysis methods.

Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study.

Journal of medical Internet research
BACKGROUND: The increasing use of social media to share lived and living experiences of substance use presents a unique opportunity to obtain information on side effects, use patterns, and opinions on novel psychoactive substances. However, due to th...

Sentiment analysis of tweets employing convolutional neural network optimized by enhanced gorilla troops optimization algorithm.

Scientific reports
Sentiment analysis has become a difficult and important task in the current world. Because of several features of data, including abbreviations, length of tweet, and spelling error, there should be some other non-conventional methods to achieve the a...

Managing emergency crises using secure information through educational awareness: COVID-19 case study.

Computers in biology and medicine
Social networks are increasingly taking over daily life, creating a volume of unsecured data and making it very difficult to capture safe data, especially in times of crisis. This study aims to use a Convolutional Neural Network (CNN)-Long Short-Term...

Perspectives surrounding robotic total hip arthroplasty: a cross-sectional analysis using natural language processing.

Canadian journal of surgery. Journal canadien de chirurgie
BACKGROUND: Robotic technology has been used in total hip arthroplasty (THA) for several years. Despite the advances in this field, perspectives surrounding robotic THA are not fully understood. This study aimed to characterize the landscape of robot...