Characterizing Anti-Vaping Posts for Effective Communication on Instagram Using Multimodal Deep Learning.

ABSTRACT:

Introduction

Instagram is a popular social networking platform for sharing photos with a large proportion of youth and young adult users. We aim to identify key features in anti-vaping Instagram image posts associated with high social media user engagement by artificial intelligence.

Aims and methods

We collected 8972 anti-vaping Instagram image posts and hand-coded 2200 Instagram images to identify nine image features such as warning signs and person-shown vaping. We utilized a deep-learning model, the OpenAI: contrastive language-image pre-training with ViT-B/32 as the backbone and a 5-fold cross-validation model evaluation, to extract similar features from the Instagram image and further trained logistic regression models for multilabel classification. Latent Dirichlet Al

SUBMITTER: Xie Z 

PROVIDER: S-EPMC10873495 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature