Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Practices related to health are circulated widely on YouTube. With a health psychology perspective, we present a study to understand health and wellbeing-related practices of a group of popular, professional YouTubers from the audio-visual content they produce. We first identify, via polytextual thematic analysis, six thematic health-related categories, and use them to label a set of 2500 YouTube videos. Agreement among three independent annotators was acceptable for these health-related categories. We then present an analysis of speech transcriptions and visual content, demonstrating that distinctive patterns exist for these health-related categories. These include linguistic markers and specific scene types and objects. Finally, with an interpretability focus, we study the feasibility of classifying health-related video categories in a binary setting, and compare performance across features, finding best accuracy for linguistic features (74-87%), and various patterns of linguistic and visual relevance used for the classification of health categories. The results shows promise to support mixed-methods research in health psychology, combining manual analysis and data-driven methods. More generally, our work contributes to the understanding of current health practices shared and promoted on social video.
Anastasios Vassilopoulos, Licai Cao