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Detecting sentiment polarities with sentilo

Capitolo di libro
Data di Pubblicazione:
2015
Abstract:
We present the tool used for the Concept-Level Sentiment Analysis Challenge ESWC-CLSA 2015 Task #1, concerning binary polarity detection of the sentiment of a sentence. Our tool is a little modification of Sentilo [7], an unsupervised, domain-independent system, previously developed by our group, that performs sentiment analysis by hybridizing natural language processing techniques with semantic web technologies. Sentilo is able to recognize the opinion holder and measure the sentiment expressed on topics and sub-topics. The knowledge extracted from the text is represented by means of an RDF graph. Holders and topics are linked to external knowledge. Sentilo is available as a REST service as well as a user-friendly demo.
Tipologia CRIS:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
sentiment analysis; sentic computing; semantic web; linked data
Elenco autori:
Mongiovì, Misael; Nuzzolese, ANDREA GIOVANNI
Autori di Ateneo:
NUZZOLESE ANDREA GIOVANNI
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/331725
Titolo del libro:
Semantic Web Evaluation Challenges
Pubblicato in:
COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE (PRINT)
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http://www.scopus.com/record/display.url?eid=2-s2.0-84951299535&origin=inward
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