Getting emotional about news summarization

Authors:
Alistair Kennedy;Anna Kazantseva;Diana Inkpen;Stan Szpakowicz
Affiliations:
School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Ontario, Canada;School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Ontario, Canada;School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Ontario, Canada;School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Ontario, Canada,Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
Venue:
Canadian AI'12 Proceedings of the 25th Canadian conference on Advances in Artificial Intelligence
Year:
2012

Citing 6
Cited 0

A binary variable model for affinity propagation

Neural Computation
The automatic creation of literature abstracts

IBM Journal of Research and Development
Summarizing blog entries versus news texts

eETTs '09 Proceedings of the Workshop on Events in Emerging Text Types
Summarizing threads in blogs using opinion polarity

eETTs '09 Proceedings of the Workshop on Events in Emerging Text Types
Evaluation of a sentence ranker for text summarization based on Roget's thesaurus

TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
Summarizing and extracting online public opinion from blog search results

DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

News is not simply a straight re-telling of events, but rather an interpretation of those events by a reporter, whose feelings and opinions can often become part of the story itself. Research on automatic summarization of news articles has thus far focused on facts rather than emotions, but perhaps emotions can be significant in news stories too. This article describes research done at the University of Ottawa to create an emotion-aware summarization system, which participated in the Text Analysis Conference last year. We have established that increasing the number of emotional words could help ranking sentences to be selected for the summary, but there was no overall improvement in the final system. Although this experiment did not improve news summarization as evaluated by a variety of standard scoring techniques, it was successful at generating summaries with more emotional words while maintaining the overall quality of the summary.