Online customer review classification and analysis have been recognized as an important
problem in many domains, such as business intelligence, marketing, and e-governance. To …

Online reviews provide rich information on customer satisfaction, displaying various numeric
ratings as well as detailed explanations presented in written form. However, analyzing this …

In recent years, with the expansion of electronic commerce, the number of customer online
reviews available on the internet is growing rapidly. Lots of online merchant's websites ask …

Analyzing product online reviews has drawn much interest in the academic field. In this
research, a new probabilistic topic model, called tag sentiment aspect models (TSA), is …

Even though the most online review systems offer star rating in addition to free text reviews,
this only applies to the overall review. However, different users may have different …

This paper investigates graph-based approaches to labeled topic clustering of reader
comments in online news. For graph-based clustering we propose a linear regression model …

The exponential growth of online social network platforms and applications has led to a
staggering volume of user-generated textual content, including comments and reviews …

Automatically identifying informative reviews is increasingly important given the rapid growth
of user generated reviews on sites like Amazon and TripAdvisor. In this paper, we describe …

Product reviews possess critical information regarding customers' concerns and their
experience with the product. Such information is considered essential to firms' business …

The authors address two novel and significant challenges in using online text reviews to
obtain attribute level ratings. First, they introduce the problem of inferring attribute level …