A Sentiment-Aware Topic Model for Extracting Failures from Product Reviews

• Published in: Text, Speech, and Dialogue pp. 37 - 45
• Main Author: Tutubalina, Elena
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing 2016
• Series: Lecture Notes in Computer Science
• Subjects: Information extraction; LDA; Mining product defects; Opinion mining; Problem phrase extraction; Topic modeling

This paper describes a probabilistic model that aims to extract different kinds of product difficulties conditioned on users’ dissatisfaction through the use of sentiment information. The proposed model learns a distribution over words, associated with topics, sentiment and problem labels. The resul...