A Novel Framework for Sentiment Based Product Recommendations Using User Reviews - A Case Study on the Steam Platform

This study aims to propose a novel framework for sentiment-based product recommendations using user reviews, with a case study on the Steam platform. In today’s digital era, user reviews have become an indispensable factor in consumers’ purchase decisions. However, traditional recommendation systems based on rating scores have certain limitations, such as the inability to capture users’ emotions and the strengths and weaknesses comprehensively. Therefore, we propose a sentiment-based product recommendation framework to better understand users’ emotional responses towards products and pro-vide personalized recommendations.