This paper presents the Topic-Aspect Model (TAM), a Bayesian mixture model which jointly discovers topics and aspects. We broadly define an aspect of a document as a characteristi...
We derive two variants of a semi-supervised model for fine-grained sentiment analysis. Both models leverage abundant natural supervision in the form of review ratings, as well as...
In this paper, we introduce the idea of Intent Analysis, which is to create a profile of the goals and intentions present in textual content. Intent Analysis, similar to Sentiment...
The aim of query-based sampling is to obtain a sufficient, representative sample of an underlying (text) collection. Current measures for assessing sample quality are too coarse gr...
Sentiment classification refers to the task of automatically identifying whether a given piece of text expresses positive or negative opinion towards a subject at hand. The prolif...