Paper: Topic-wise Sentiment-wise or Otherwise? Identifying the Hidden Dimension for Unsupervised Text Classification

ACL ID D09-1061
Title Topic-wise Sentiment-wise or Otherwise? Identifying the Hidden Dimension for Unsupervised Text Classification
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009
Authors

While traditional work on text clustering has largely focused on grouping docu- ments by topic, it is conceivable that a user may want to cluster documents along other dimensions, such as the author’s mood, gender, age, or sentiment. Without know- ing the user’s intention, a clustering al- gorithm will only group documents along the most prominent dimension, which may not be the one the user desires. To ad- dress this problem, we propose a novel way of incorporating user feedback into a clustering algorithm, which allows a user to easily specify the dimension along which she wants the data points to be clus- tered via inspecting only a small number of words. This distinguishes our method from existing ones, which typically re- quire a large amount of effort on the part of humans in the...