A Semantic Web Based Core Engine to Efficiently Perform Sentiment Analysis

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• 作者：Diego Reforgiato Recupero (7)
  Sergio Consoli (7)
  Aldo Gangemi (7) (8)
  Andrea Giovanni Nuzzolese (7) (9)
  Daria Spampinato (7)
  
• 关键词：Sentic computing ; Sentiment analysis ; Semantic features
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：1
• 期：1
• 页码：245-248
• 全文大小：631 KB
• 参考文献：1. Bing, L.: Sentiment analysis and subjectivity. In: Invited Chapter for the Handbook of Natural Language Processing (2010)
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  10. Saif, H., He, Y., Alani, H.: Semantic sentiment analysis of twitter. In: Cudr茅-Mauroux, P., Heflin, J., Sirin, E., Tudorache, T., Euzenat, J., Hauswirth, M., Parreira, J.X., Hendler, J., Schreiber, G., Bernstein, A., Blomqvist, E. (eds.) ISWC 2012, Part I. LNCS, vol. 7649, pp. 508鈥?24. Springer, Heidelberg (2012) CrossRef
  
• 作者单位：Diego Reforgiato Recupero (7)
  Sergio Consoli (7)
  Aldo Gangemi (7) (8)
  Andrea Giovanni Nuzzolese (7) (9)
  Daria Spampinato (7)
  
  7. STLab-ISTC Consiglio Nazionale delle Ricerche, Rome, Italy
  8. LIPN, University Paris 13, Sorbone Cit鈥榚, UMR CNRS, Paris, France
  9. Department of Computer Science and Engineering, University of Bologna, Bologna, Italy
  
• ISSN：1611-3349

文摘

In this paper we present a domain-independent framework that creates a sentiment analysis model by mixing Semantic Web technologies with natural language processing approaches (This work is supported by the project PRISMA SMART CITIES, funded by the Italian Ministry of Research and Education under the program PON.). Our system, called Sentilo, provides a core sentiment analysis engine which fully exploits semantics. It identifies the holder of an opinion, topics and sub-topics the opinion is referred to, and assesses the opinion trigger. Sentilo uses an OWL opinion ontology to represent all this information with an RDF graph where holders and topics are resolved on Linked Data. Anyone can plug its own opinion scoring algorithm to compute scores of opinion expressing words and come up with a combined scoring algorithm for each identified entities and the overall sentence.