AI RESEARCH

Enhancing Game Review Sentiment Classification on Steam Platform with Attention-Based BiLSTM

arXiv CS.CL

ArXi:2605.01315v1 Announce Type: new This paper investigates sentiment classification of Steam game reviews using an attention-based Bidirectional Long Short-Term Memory (BiLSTM) model. Using a dataset of 50,000 reviews sampled from a larger Steam review corpus, the authors compare a traditional machine learning baseline based on TF-IDF and PyCaret AutoML with a deep learning approach implemented in PyTorch.