Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91739
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Computingen_US
dc.creatorZeng, JCen_US
dc.creatorLi, Jen_US
dc.creatorHe, YLen_US
dc.creatorGao, CYen_US
dc.creatorLyu, MRen_US
dc.creatorKing, Ren_US
dc.date.accessioned2021-12-01T02:43:15Z-
dc.date.available2021-12-01T02:43:15Z-
dc.identifier.isbn978-1-4503-7023-3 (eisbn)en_US
dc.identifier.urihttp://hdl.handle.net/10397/91739-
dc.language.isoenen_US
dc.publisherInternational World Wide Web Conference Committeeen_US
dc.rightsThis paper is published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license. Authors reserve their rights to disseminate the work on their personal and corporate Web sites with the appropriate attribution.en_US
dc.rights© 2020 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Jichuan Zeng, Jing Li, Yulan He, Cuiyun Gao, Michael R. Lyu, and Irwin King. 2020. What Changed Your Mind: The Roles of Dynamic Topics and Discourse in Argumentation Process. In Proceedings of The Web Conference 2020 (WWW ’20), April 20–24, 2020, Taipei, Taiwan. ACM, New York, NY, USA, 12 pages is available at https://doi.org/10.1145/3366423.3380223en_US
dc.subjectSocial mediaen_US
dc.subjectArgumentation miningen_US
dc.subjectTopic modelingen_US
dc.subjectDiscourse modelingen_US
dc.subjectDynamic data processingen_US
dc.titleWhat changed your mind : the roles of dynamic topics and discourse in argumentation processen_US
dc.typeConference Paperen_US
dc.identifier.spage1502en_US
dc.identifier.epage1513en_US
dc.identifier.doi10.1145/3366423.3380223en_US
dcterms.abstractIn our world with full of uncertainty, debates and argumentation contribute to the progress of science and society. Despite of the increasing attention to characterize human arguments, most progress made so far focus on the debate outcome, largely ignoring the dynamic patterns in argumentation processes. This paper presents a study that automatically analyzes the key factors in argument persuasiveness, beyond simply predicting who will persuade whom. Specifically, we propose a novel neural model that is able to dynamically track the changes of latent topics and discourse in argumentative conversations, allowing the investigation of their roles in influencing the outcomes of persuasion. Extensive experiments have been conducted on argumentative conversations on both social media and supreme court. The results show that our model outperforms state-of-the-art models in identifying persuasive arguments via explicitly exploring dynamic factors of topic and discourse. We further analyze the effects of topics and discourse on persuasiveness, and find that they are both useful - topics provide concrete evidence while superior discourse styles may bias participants, especially in social media arguments. In addition, we draw some findings from our empirical results, which will help people better engage in future persuasive conversations.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIn The Web Conference 2020 : proceedings of the World Wide Web Conference WWW 2020 : Taipei 2020 : April 20-24, 2020, Taipei, Taiwan, p. 1502-1513en_US
dcterms.issued2020-04-20-
dc.identifier.isiWOS:000626273301051-
dc.identifier.scopus2-s2.0-85086598924-
dc.relation.ispartofbookThe Web Conference 2020 : proceedings of the World Wide Web Conference WWW 2020 : Taipei 2020 : April 20-24, 2020, Taipei, Taiwanen_US
dc.relation.conferenceWeb Conference (WWW)en_US
dc.description.validate202112 bcwhen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Others-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe work described in this paper is supported by the Research Grants Council of the Hong Kong Special Administrative Region, China (No. CUHK 14210717 of the General Research Fund and No. CUHK 2410021 of the Research Impact Fund R5034-18). Jing Li is supported by the Hong Kong Polytechnic University Internal Fund (1-BE2W). YH is partly funded by the EPSRC grant EP/T017112/1.en_US
dc.description.pubStatusPublisheden_US
Appears in Collections:Conference Paper
Files in This Item:
File Description SizeFormat 
3366423.3380223.pdf1.44 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

95
Last Week
0
Last month
Citations as of Mar 24, 2024

Downloads

66
Citations as of Mar 24, 2024

SCOPUSTM   
Citations

13
Citations as of Mar 28, 2024

WEB OF SCIENCETM
Citations

6
Citations as of Mar 28, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.