Indeed, these methods theoretically make use of combined features from both textual and categorical features, which make them more powerful than disconnected features.
metadata is generated for human understanding, and thus we claim that these categories need to be carefully represented for machine use to Figure 1: A high-level framework of models for the Customized Text Classification Task that inputs a text with n tokens (e.g., review) and m categories (e.g., users, products) and outputs a class (e.g., positive/negative).