Aker, A., Kurtic, E., Hepple, M. et al. (2 more authors) (2015) Comment-to-Article Linking in the Online News Domain. In: Proceedings of the SIGDIAL 2015 Conference. SigDial, 02-04 Sep 2015, Prague. ACL , pp. 245-249.
Abstract
Online commenting to news articles pro- vides a communication channel between media professionals and readers offering a crucial tool for opinion exchange and free- dom of expression. Currently, comments are detached from the news article and thus removed from the context that they were written for. In this work, we propose a method to connect readers’ comments to the news article segments they refer to. We use similarity features to link comments to relevant article segments and evaluate both word-based and term-based vector spaces. Our results are comparable to state-of-the- art topic modeling techniques when used for linking tasks. We demonstrate that arti- cle segments and comments representation are relevant to linking accuracy since we achieve better performances when similar- ity features are computed using similarity between terms rather than words.
Metadata
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Copyright, Publisher and Additional Information: | © 2015 Association for Computational Linguistics. Article licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License (https://creativecommons.org/licenses/by-nc-sa/3.0/). Permission is granted to make copies for the purposes of teaching and research | ||||
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Institution: | The University of Sheffield | ||||
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) | ||||
Funding Information: |
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Depositing User: | Symplectic Sheffield | ||||
Date Deposited: | 16 Aug 2016 08:20 | ||||
Last Modified: | 19 Dec 2022 13:33 | ||||
Published Version: | https://www.aclweb.org/anthology/W/W15/W15-4635.pd... | ||||
Status: | Published | ||||
Publisher: | ACL | ||||
Refereed: | Yes |