Identifying Pros and Cons of Product Aspects Based on Customer Reviews
Ebad Ahmadzadeh, Philip K. Chan · 2018
The task of identifying pros and cons from product reviews has applications in decision support for consumers. It becomes even more useful when the pros and cons are identified for product aspects so consumers can quickly see strengths and weaknesses of each aspect of the product without reading all reviews. Given a collection of product reviews, we automatically extract relevant product aspects, find the most significant sentences that represent pros and cons for each aspect, and provide a summary for each aspect. We introduce SS2 to select sentences that are likely to represent pros/cons and are semantically related to the aspect to which they are associated. Our results on three data sets indicate that compared to an existing algorithm, our algorithm can generate more meaningful summarized aspects, along with a list of pros and cons more closely related to each aspect.