Paper Info
Title
The SENSEI Overview of Newspaper Readers' Comments.
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.
Year
DOI
Venue
2017
10.1007/978-3-319-56608-5_77
ADVANCES IN INFORMATION RETRIEVAL, ECIR 2017
Keywords
Field
DocType
User interface,Summarization,Newspaper,Social media
Automatic summarization,Data mining,World Wide Web,Social media,Information retrieval,Viewpoints,Computer science,Newspaper,User interface
Conference
Volume
ISSN
Citations 
10193
0302-9743
0
PageRank 
References 
Authors
0.34
5
6
Name
Order
Citations
PageRank
Adam Funk131417.90
Ahmet Aker226730.75
Emma Barker3356.86
Monica Lestari Paramita420713.65
Mark Hepple570275.09
Robert Gaizauskas6923121.46