Deep Learning Approaches for Twitter User Classification

Abstract

 Twitter, a popular social media platform,  has become a rich source of user-generated content. The  classification of Twitter users based on their characteristics  and behavior has gained significant attention. Deep learning  techniques, with their ability to capture complex patterns and  representations, have emerged as powerful tools for Twitter  user classification. This research article presents a compre hensive review of deep learning approaches for Twitter user  classification. We discuss various deep learning architec 

tures, pretraining techniques, and transfer learning strategies  used in the classification task. Through a thorough analysis  of existing studies, we highlight the strengths and limitations  of deep learning approaches and provide recommendations  for future research in this field.