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Hierarchical viewpoint discovery from tweets using Bayesian modelling
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Zhu, Lixing, He, Yulan and Zhou, Deyu (2019) Hierarchical viewpoint discovery from tweets using Bayesian modelling. Expert Systems with Applications, 116 . pp. 430-438. doi:10.1016/j.eswa.2018.09.028 ISSN 0957-4174.
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WRAP-hierarchical-viewpoint-discovery-tweets-Bayesian-modelling-He-2018.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (2143Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.eswa.2018.09.028
Abstract
When users express their stances towards a topic in social media, they might elaborate their viewpoints or reasoning. Oftentimes, viewpoints expressed by different users exhibit a hierarchical structure. Therefore, detecting this kind of hierarchical viewpoints offers a better insight to understand the public opinion. In this paper, we propose a novel Bayesian model for hierarchical viewpoint discovery from tweets. Driven by the motivation that a viewpoint expressed in a tweet can be regarded as a path from the root to a leaf of a hierarchical viewpoint tree, the assignment of the relevant viewpoint topics is assumed to follow two nested Chinese restaurant processes. Moreover, opinions in text are often expressed in un-semantically decomposable multi-terms or phrases, such as ‘economic recession’. Hence, a hierarchical Pitman–Yor process is employed as a prior for modelling the generation of phrases with arbitrary length. Experimental results on two Twitter corpora demonstrate the effectiveness of the proposed Bayesian model for hierarchical viewpoint discovery.
Item Type: | Journal Article | |||||||||||||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | |||||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | |||||||||||||||
Library of Congress Subject Headings (LCSH): | Natural language processing (Computer science), Social media, Public opinion | |||||||||||||||
Journal or Publication Title: | Expert Systems with Applications | |||||||||||||||
Publisher: | Pergamon-Elsevier Science Ltd. | |||||||||||||||
ISSN: | 0957-4174 | |||||||||||||||
Official Date: | February 2019 | |||||||||||||||
Dates: |
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Volume: | 116 | |||||||||||||||
Page Range: | pp. 430-438 | |||||||||||||||
DOI: | 10.1016/j.eswa.2018.09.028 | |||||||||||||||
Status: | Peer Reviewed | |||||||||||||||
Publication Status: | Published | |||||||||||||||
Access rights to Published version: | Restricted or Subscription Access | |||||||||||||||
Date of first compliant deposit: | 8 October 2018 | |||||||||||||||
Date of first compliant Open Access: | 13 September 2019 | |||||||||||||||
RIOXX Funder/Project Grant: |
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