Abstract: Method for analyzing review content is described herein. The method starts by generating a helpfulness score for each review in the plurality of reviews. A first set of reviews is selected based on the helpfulness scores for each review in the plurality of review and a helpfulness score for each sentence in each review in the first set of reviews is generated. The review summary is then generated by selecting sentences in each review in the first set of reviews based on the helpfulness score of each sentence. The review summary includes the selected sentences. Other embodiments are also described.

Abstract: In various example embodiments, a system and method for evaluating and sorting product feedback is presented. In one example, a system includes a learning module to train a machine learning system on feedback from a plurality of users, the machine learning system configured to generate a quality rating for individual feedback, a feedback module to collect feedback for a specific product available from the online network based marketplace and apply the machine learning system to generate a quality rating for each feedback collected, and a sorting module to sort the feedback collected according to the quality ratings generated by the machine learning system.