Funk, A., Aker, A., Barker, E. et al. (3 more authors) (2017) The SENSEI Overview of Newspaper Readers’ Comments. In: Jose, J.M., Hauff, C., Alt ingovde, I.S., Song, D., Albakour, D., Watt, S. and Tait, J., (eds.) Advances in Information Retrieval. ECIR 2017. 39th European Conference on IR Research, ECIR 2017, 08-13 Apr 2017, Aberdeen, UK. Lecture Notes in Computer Science (10193). Springer , pp. 758-761. ISBN 978-3-319-56608-5
Abstract
Automatic summarization of reader comments in on-line news is a challenging but clearly useful task. Work to date has produced extractive summaries using well-known techniques from other areas of NLP. But do users really want these, and do they support users in realistic tasks? We specify an alternative summary type for reader comments, based on the notions of issues and viewpoints, and demonstrate our user interface to present it. An evaluation to assess how well summarization systems support users in time-limited tasks (identifying issues and characterizing opinions) gives good results for this prototype.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © Springer, 2017. This is an author produced version of a paper subsequently published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | User interface; summarization; newspaper; social media |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - FP6/FP7 SENSEI - 610916 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 16 Jun 2017 12:19 |
Last Modified: | 23 Nov 2017 15:19 |
Published Version: | http://dx.doi.org/10.1007/978-3-319-56608-5_77 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-319-56608-5_77 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:117787 |