Pradnya Bhagat


2023

pdf
ReviewCraft : A Word2Vec Driven System Enhancing User-Written Reviews
Gaurav Sawant | Pradnya Bhagat | Jyoti D. Pawar
Proceedings of the 20th International Conference on Natural Language Processing (ICON)

The significance of online product reviews has become indispensable for customers in making informed buying decisions, while e-commerce platforms use them to fine tune their recommender systems. However, since review writing is purely a voluntary process without any incentives, most customers opt out from writing reviews or write poor-quality ones. This lack of engagement poses credibility issues as fake or biased reviews can mislead buyers who rely on them for informed decision-making. To address this issue, this paper introduces a system that suggests product features and appropriate sentiment words to help users write informative product reviews in a structured manner. The system is based on Word2Vec model and Chi square test. The evaluation results demonstrates that the reviews with recommendations showed a 2 fold improvement both, in the quality of the features covered and correct usage of sentiment words, as well as a 19% improvement in overall usefulness compared to reviews without recommendations. Keywords: Word2Vec, Chi-square, Sentiment words, Product Aspect/Feature.