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 sentimentbased 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-oriented information retrieval: Affective analysis of documents based on the SenticNet framework
BISIO, FEDERICA;MEDA, CLAUDIA;GASTALDO, PAOLO;ZUNINO, RODOLFO;
2016-01-01
Abstract
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 sentimentbased 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.
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