Sciweavers

Share
ECIR
2016
Springer

VODUM: A Topic Model Unifying Viewpoint, Topic and Opinion Discovery

4 years 3 months ago
VODUM: A Topic Model Unifying Viewpoint, Topic and Opinion Discovery
The surge of opinionated on-line texts provides a wealth of information that can be exploited to analyze users’ viewpoints and opinions on various topics. This article presents VODUM, an unsupervised Topic Model designed to jointly discover viewpoints, topics, and opinions in text. We hypothesize that partitioning topical words and viewpointspecific opinion words using part-of-speech helps to discriminate and identify viewpoints. Quantitative and qualitative experiments on the Bitterlemons collection show the performance of our model. It outperforms state-of-the-art baselines in generalizing data and identifying viewpoints. This result stresses how important topical and opinion words separation is, and how it impacts the accuracy of viewpoint identification.
Thibaut Thonet, Guillaume Cabanac, Mohand Boughane
Added 02 Apr 2016
Updated 02 Apr 2016
Type Journal
Year 2016
Where ECIR
Authors Thibaut Thonet, Guillaume Cabanac, Mohand Boughanem, Karen Pinel-Sauvagnat
Comments (0)
books