Sentiment analysis of user-generated online content

Bobicev Victoria; Sokolova Marina

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2021-06-11 19:10

SM ISO690:2012

BOBICEV, Victoria, SOKOLOVA, Marina. Sentiment analysis of user-generated online content. In: Telecommunications, Electronics and Informatics, Ed. 5, 20-23 mai 2015, Chișinău. Chișinău, Republica Moldova: 2015, Ed. 5, pp. 335-338. ISBN 978-9975-45-377-6.

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Telecommunications, Electronics and Informatics
Ed. 5, 2015

Conferința "Telecommunications, Electronics and Informatics"
5, Chișinău, Moldova, 20-23 mai 2015

Sentiment analysis of user-generated online content

Pag. 335-338

Bobicev Victoria¹, Sokolova Marina²

¹ Technical University of Moldova,
² University of Ottawa

Disponibil în IBN: 22 mai 2018

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Rezumat

This paper presents several experiments in the domain of automate text sentiment analysis. Comparison between machine learning (ML) and rule-based algorithms demonstrated that well-tuned rule-based methods obtain better results than general ML methods and it is necessary to use various types of features for obtaining satisfactory accuracy using ML algorithms.

Cuvinte-cheie
Natural Language Pricessing, Rule – based methods, Semantic Lexicons,

text analysis, sentiment analysis, Machine Learning Algorithms

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