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Visualizing Sentiment Analysis on a User Forum

Sundberg, Rasmus LU ; Eriksson, Anders ; Bini, Johan and Nugues, Pierre LU orcid (2012) The eighth international conference on Language Resources and Evaluation (LREC 2012) p.3573-3579
Abstract
Sentiment analysis, or opinion mining, is the process of extracting sentiment from documents or sentences, where the expressed sentiment is typically categorized as positive, negative, or neutral. Many different techniques have been proposed. In this paper, we report the reimplementation of nine algorithms and their evaluation across four corpora to assess the sentiment at the sentence level. We extracted the named entities from each sentence and we associated them with the sentence sentiment. We built a graphical module based on the Qlikview software suite to visualize the sentiments attached to named entities mentioned in Internet forums and follow opinion changes over time.
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Proceedings of the eighth international conference on Language Resources and Evaluation (LREC 2012)
pages
3573 - 3579
publisher
European Language Resources Association
conference name
The eighth international conference on Language Resources and Evaluation (LREC 2012)
conference location
Istanbul, Turkey
conference dates
2012-05-21 - 2012-05-27
external identifiers
  • wos:000323927703106
  • scopus:84979660074
ISBN
978-2-9517408-7-7
language
English
LU publication?
yes
id
a0cd4d79-05f1-418e-94be-24b232af080a (old id 2972004)
alternative location
http://www.lrec-conf.org/proceedings/lrec2012/pdf/453_Paper.pdf
date added to LUP
2016-04-04 10:26:15
date last changed
2022-03-23 08:01:48
@inproceedings{a0cd4d79-05f1-418e-94be-24b232af080a,
  abstract     = {{Sentiment analysis, or opinion mining, is the process of extracting sentiment from documents or sentences, where the expressed sentiment is typically categorized as positive, negative, or neutral. Many different techniques have been proposed. In this paper, we report the reimplementation of nine algorithms and their evaluation across four corpora to assess the sentiment at the sentence level. We extracted the named entities from each sentence and we associated them with the sentence sentiment. We built a graphical module based on the Qlikview software suite to visualize the sentiments attached to named entities mentioned in Internet forums and follow opinion changes over time.}},
  author       = {{Sundberg, Rasmus and Eriksson, Anders and Bini, Johan and Nugues, Pierre}},
  booktitle    = {{Proceedings of the eighth international conference on Language Resources and Evaluation (LREC 2012)}},
  isbn         = {{978-2-9517408-7-7}},
  language     = {{eng}},
  pages        = {{3573--3579}},
  publisher    = {{European Language Resources Association}},
  title        = {{Visualizing Sentiment Analysis on a User Forum}},
  url          = {{https://lup.lub.lu.se/search/files/5538738/2972005.pdf}},
  year         = {{2012}},
}