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

Thonet, Thibaut and Cabanac, Guillaume and Boughanem, Mohand and Pinel-Sauvagnat, Karen VODUM: a Topic Model Unifying Viewpoint, Topic and Opinion Discovery. (2016) In: 38th European Conference on Information Retrieval (ECIR 2016), 20 March 2016 - 23 March 2016 (Padua, Italy).

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Official URL: http://dx.doi.org/10.1007/978-3-319-30671-1_39

Abstract

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 viewpoint-specific 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.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to Springer editor. This papers appears in Volume 9626 of Lecture Notes in Computer Science ISSN : 0302-9743 The original PDF is available at: https://link.springer.com/chapter/10.1007/978-3-319-30671-1_39
HAL Id:hal-01567069
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited By: IRIT IRIT
Deposited On:27 Jun 2017 13:49

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