Login / Signup

Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study.

William BakerJason B ColditzPage Daniel DobbsHuy MaiShyam VisweswaranJustin ZhanBrian A Primack
Published in: JMIR medical informatics (2022)
Large, open-source deep learning classifiers, such as BERTweet, can provide researchers the ability to reliably determine if tweets are relevant to vaping; include commercial content; and include positive, negative, or neutral content about vaping with a higher accuracy than traditional natural language processing deep learning models. Such enhancement to the utilization of Twitter data can allow for faster exploration and dissemination of time-sensitive data than traditional methodologies (eg, surveys, polling research).
Keyphrases
  • deep learning
  • artificial intelligence
  • social media
  • convolutional neural network
  • big data
  • machine learning
  • electronic health record
  • cross sectional
  • data analysis