Semantic Spaces for Sentiment Analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F13%3A43919420" target="_blank" >RIV/49777513:23520/13:43919420 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-40585-3_61" target="_blank" >http://dx.doi.org/10.1007/978-3-642-40585-3_61</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-40585-3_61" target="_blank" >10.1007/978-3-642-40585-3_61</a>
Alternative languages
Result language
angličtina
Original language name
Semantic Spaces for Sentiment Analysis
Original language description
This article presents a new semi-supervised method for document-level sentiment analysis. We employ a supervised state-of-the-art classification approach and enrich the feature set by adding word cluster features. These features exploit clusters of wordsrepresented in semantic spaces computed on unlabeled data. We test our method on three large sentiment datasets (Czech movie and product reviews, and English movie reviews) and outperform the current state of the art. To the best of our knowledge, thisarticle reports the first successful incorporation of semantic spaces based on local word co-occurrence in the sentiment analysis task.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
TSD 2013
ISBN
978-3-642-40584-6
ISSN
0302-9743
e-ISSN
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Number of pages
8
Pages from-to
484-491
Publisher name
Springer
Place of publication
Berlin
Event location
Plzeň
Event date
Sep 1, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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