CQAVis: Visual text analytics for community question answering

Enamul Hoque, Shafiq Rayhan Joty, Lluis Marques, Giuseppe Carenini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Community question answering (CQA) forums can provide effective means for sharing information and addressing a user's information needs about particular topics. However, many such online forums are not moderated, resulting in many low quality and redundant comments, which makes it very challenging for users to find the appropriate answers to their questions. In this paper, we apply a user-centered design approach to develop a system, CQAVis, which supports users in identifying high quality comments and get their questions answered. Informed by the user's requirements, the system combines both text analytics and interactive visualization techniques together in a synergistic way. Given a new question posed by the user, the text analytic module automatically finds relevant answers by exploring existing related questions and the comments within their threads. Then the visualization module presents the search results to the user and supports the exploration of related comments. We have evaluated the system in the wild by deploying it within a CQA forum among thousands of real users. Through the online study, we gained deeper insights about the potential utility of the system, as well as learned generalizable lessons for designing visual text analytics systems for the domain of CQA forums.

Original languageEnglish
Title of host publicationIUI 2017 - Proceedings of the 22nd International Conference on Intelligent User Interfaces
PublisherAssociation for Computing Machinery
Pages161-172
Number of pages12
VolumePart F126745
ISBN (Electronic)9781450343480
DOIs
Publication statusPublished - 7 Mar 2017
Event22nd International Conference on Intelligent User Interfaces, IUI 2017 - Limassol, Cyprus
Duration: 13 Mar 201716 Mar 2017

Other

Other22nd International Conference on Intelligent User Interfaces, IUI 2017
CountryCyprus
CityLimassol
Period13/3/1716/3/17

Fingerprint

Visualization
User centered design

Keywords

  • Asynchronous conversation
  • Community question answering
  • Computer-mediated communication
  • Text visualization

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction

Cite this

Hoque, E., Rayhan Joty, S., Marques, L., & Carenini, G. (2017). CQAVis: Visual text analytics for community question answering. In IUI 2017 - Proceedings of the 22nd International Conference on Intelligent User Interfaces (Vol. Part F126745, pp. 161-172). Association for Computing Machinery. https://doi.org/10.1145/3025171.3025210

CQAVis : Visual text analytics for community question answering. / Hoque, Enamul; Rayhan Joty, Shafiq; Marques, Lluis; Carenini, Giuseppe.

IUI 2017 - Proceedings of the 22nd International Conference on Intelligent User Interfaces. Vol. Part F126745 Association for Computing Machinery, 2017. p. 161-172.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hoque, E, Rayhan Joty, S, Marques, L & Carenini, G 2017, CQAVis: Visual text analytics for community question answering. in IUI 2017 - Proceedings of the 22nd International Conference on Intelligent User Interfaces. vol. Part F126745, Association for Computing Machinery, pp. 161-172, 22nd International Conference on Intelligent User Interfaces, IUI 2017, Limassol, Cyprus, 13/3/17. https://doi.org/10.1145/3025171.3025210
Hoque E, Rayhan Joty S, Marques L, Carenini G. CQAVis: Visual text analytics for community question answering. In IUI 2017 - Proceedings of the 22nd International Conference on Intelligent User Interfaces. Vol. Part F126745. Association for Computing Machinery. 2017. p. 161-172 https://doi.org/10.1145/3025171.3025210
Hoque, Enamul ; Rayhan Joty, Shafiq ; Marques, Lluis ; Carenini, Giuseppe. / CQAVis : Visual text analytics for community question answering. IUI 2017 - Proceedings of the 22nd International Conference on Intelligent User Interfaces. Vol. Part F126745 Association for Computing Machinery, 2017. pp. 161-172
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