In this paper, we propose a review selection approach towards accurate estimation of feature ratings for services on participatory websites where users write textual reviews for t...
We develop a general method to match unstructured text reviews to a structured list of objects. For this, we propose a language model for generating reviews that incorporates a de...
Nilesh N. Dalvi, Ravi Kumar, Bo Pang, Andrew Tomki...
Online reviews are widely used for purchase decisions. Their trustworthiness is limited, however, by fake reviews. Fortunately, opinions from friends in a social network are more ...
For languages with rich content over the web, business reviews are easily accessible via many known websites, e.g., Yelp.com. For languages with poor content over the web like Arab...
Existing works on sentiment analysis on product reviews suffer from the following limitations: (1) The knowledge of hierarchical relationships of products attributes is not fully ...
This paper revisits an aspect of citation theory (i.e., citer motivation) with respect to the Mathematical Review system and the reviewer’s role in mathematics. We focus on a se...
Assessing the trustworthiness of reviews is a key issue for the maintainers of opinion sites such as TripAdvisor, given the rewards that can be derived from posting false or biase...
The Web has plenty of reviews, comments and reports about products, services, government policies, institutions, etc. The opinions expressed in these reviews influence how people...
Eduard C. Dragut, Clement T. Yu, A. Prasad Sistla,...
This paper presents a simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended (thumbs down). The classification of a review is...
We present two methods for determining the sentiment expressed by a movie review. The semantic orientation of a review can be positive, negative, or neutral. We examine the effect...