Topic modeling and social network analysis approach to explore diabetes discourse on Twitter in India - Ramamoorthy, Thilagavathi; Kulothungan, Vaitheeswaran; Mappillairaju, Bagavandas (Frontiers in Artificial Intelligence, 2024)
Introduction: The utilization of social media presents a promising avenue for the prevention and management of diabetes. To cater to the diabetes-related knowledge, support, and intervention needs of the community effectively, it is imperative to attain a deeper understanding of the extent and content of discussions pertaining to this health issue. This study aims to assess and compare various topic modeling techniques to determine the most effective model for identifying the core themes in diabetes-related tweets, the sources responsible for disseminating this information, the reach of these themes, and the influential individuals within the Twitter community in India.Methods: Twitter messages from India, dated between November 7, 2022, and February 28, 2023, were collected using the Twitter API. The unsupervised machine learning topic models namely Latent Dirichlet allocation (LDA), Non-negative matrix factorization (NMF), BERTopic and Top2Vec were compared and the best performing model was used to identify common diabetes-related topics. Influential users were identified through social network analysis.Results: NMF model outperformed LDA model, whereas BERTopic performed better than Top2Vec. Diabetes related conversations revolved around 8 topics namely promotion, management, drug and personal story, consequences, risk factors and research, raising awareness, and providing support, diet, opinion and lifestyle changes. The influential nodes identified were mainly health professionals and healthcare organisations.Discussion: The study identified important topics of discussion, health professionals and healthcare organisations involved in sharing diabetes related information to public. The collaborations between the influential healthcare organisations, health professionals and government can foster awareness and prevention of noncommunicable diseases.