An efficient analysis pipeline, integrating topic modeling with large language model (LLM) summarizing and human verification, was applied to identify the discussion topics. Results: We analyzed 1765 ...

Abstract: With the rapid growth of digital technologies and machine learning methods in recent years, governments have the opportunity to analyse and collect citizens’ feedback, which is usually ...

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts ...

Introduction: The convergence of AI, entrepreneurship, and online education has accelerated, yet their intersection remains under-mapped. Methods: We analyzed 489 peer-reviewed articles (2010–2024) ...

Abstract: In the highly competitive culinary industry, especially in fast-growing markets like Bandung, understanding customer preferences and experiences is essential for business survival. This ...

Objective Comprehensive data and analyses on cardiovascular research could clarify recent research trends for the academic community and facilitate policy development. We examined publications and ...

Dr. McBain studies policies and technologies that serve vulnerable populations. On any given night, countless teenagers confide in artificial intelligence chatbots — sharing their loneliness, anxiety ...

Topic modelling, primarily using Latent Dirichlet Allocation (LDA) algorithm, was employed to uncover latent themes in patient feedback, compare patient experiences across different healthcare ...

Add a description, image, and links to the topic-modelling topic page so that developers can more easily learn about it.

Analyze hospital reviews using topic modeling (LDA) and sentiment analysis (XGBoost). This NLP project uncovers key themes in patient feedback and predicts sentiment to support healthcare service ...

Background: Psycho-linguistic and audio data derived from speech may be useful in screening and monitoring cognitive aging. However, there are gaps in understanding the predictive value of different ...