Online Review

Online reviews are a rich source of data for understanding consumer sentiment and preferences, driving research focused on efficiently extracting actionable insights. Current research employs advanced natural language processing techniques, including transformer models like BERT and T5, and capsule networks, often augmented by sentiment lexicons, to analyze review text and predict helpfulness. This work is crucial for improving product design, dynamic pricing strategies, and recommendation systems, ultimately enhancing both business decision-making and consumer experiences. Furthermore, understanding cultural nuances in reviews is emerging as a key area of investigation to improve the accuracy and fairness of these analytical methods.