1.

Record Nr.

UNINA9910253868203321

Autore

Biagioni Raoul

Titolo

The SenticNet Sentiment Lexicon: Exploring Semantic Richness in Multi-Word Concepts / / by Raoul Biagioni

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016

ISBN

3-319-38971-8

Edizione

[1st ed. 2016.]

Descrizione fisica

1 online resource (VI, 55 p. 13 illus., 8 illus. in color.)

Collana

SpringerBriefs in Cognitive Computation, , 2212-6023 ; ; 4

Disciplina

401.430285

Soggetti

Neurosciences

Natural language processing (Computer science)

Semantics

Natural Language Processing (NLP)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references at the end of each chapters and index.

Nota di contenuto

Introduction -- Sentiment Analysis -- SenticNet -- Unsupervised Sentiment Classification -- Evaluation -- Conclusion -- Index. .

Sommario/riassunto

The research and its outcomes presented in this book, is about lexicon-based sentiment analysis. It uses single-, and multi-word concepts from the SenticNet sentiment lexicon as the source of sentiment information for the purpose of sentiment classification. In 6 chapters the book sheds light on the comparison of sentiment classification accuracy between single-word and multi-word concepts, for which a bespoke sentiment analysis system developed by the author was used. This book will be of interest to students, educators and researchers in the field of Sentic Computing.