A Fuzzy Approach to Sentiment Analysis at the Sentence Level

Date

2021-05-05

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

Springer International Publishing

Type

Book chapter

Peer reviewed

Yes

Abstract

The objective of this chapter is to present a hybrid approach to the Sentiment Analysis problem focused on sentences or snippets. This new method is centred around a sentiment lexicon enhanced with the assistance of SentiWordNet and fuzzy sets to estimate the semantic orientation polarity and intensity for sentences. This provides a foundation for computing with sentiments. The proposed hybrid method is applied to three different datasets and the results achieved are compared to those obtained using Naïve Bayes (NB) and Maximum Entropy (ME) techniques. It is demonstrated through experimentation that this hybrid approach is more accurate and precise than both NB and ME techniques. Furthermore, it is shown that when applied to datasets containing snippets, the proposed method performs similar to state-of-the-art techniques.

Description

Keywords

Sentiment analysis, Hybrid method, Fuzzy sets, Fuzzy methods, Machine learning, Computing with sentiments

Citation

Appel, O., Chiclana, F., Carter, J. and Fujita, H. (2021) A Fuzzy Approach to Sentiment Analysis at the Sentence Level. In: Jenny Carter, Francisco Chiclana, Arjab Singh Khuman, Tianhua Chen (Eds.):Fuzzy Logic: Recent Applications and Developments. Springer International Publishing, pp. 11-34

Rights

Research Institute

Institute of Artificial Intelligence (IAI)