Sentiment-Oriented Information Retrieval: Affective Analysis of Documents Based on the SenticNet Framework

  • Federica BisioEmail author
  • Claudia Meda
  • Paolo Gastaldo
  • Rodolfo Zunino
  • Erik Cambria
Part of the Studies in Computational Intelligence book series (SCI, volume 639)


Sentiment analysis research has acquired a growing importance due to its applications in several different fields. A large number of companies have included the analysis of opinions and sentiments of costumers as a part of their mission. Therefore, the analysis and automatic classification of large corpora of documents in natural language, based on the conveyed feelings and emotions, has become a crucial issue for text mining purposes. This chapter aims to relate the sentiment-based characterization inferred from books with the distribution of emotions within the same texts. The main result consists in a method to compare and classify texts based on the feelings expressed within the narrative trend.


Sentiment analysis Text mining Senticnet SLAIR 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Federica Bisio
    • 1
    Email author
  • Claudia Meda
    • 1
  • Paolo Gastaldo
    • 1
  • Rodolfo Zunino
    • 1
  • Erik Cambria
    • 2
  1. 1.DITEN – University of GenoaGenoaItaly
  2. 2.SCE – School of Computer Engineering, Nanyang Technological UniversitySingaporeSingapore

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