A Hybrid Approach to Sentiment Analysis with Benchmarking Results

Date

2016

Advisors

Journal Title

Journal ISSN

ISSN

DOI

Volume Title

Publisher

Springer Lectures Notes Computer Science

Type

Conference

Peer reviewed

Yes

Abstract

The objective of this article is two-fold. Firstly, a hybrid approach to Sentiment Analysis encompassing the use of Semantic Rules, Fuzzy Sets and an enriched Sentiment Lexicon, improved with the support of SentiWordNet is described. Secondly, the proposed hybrid method is compared against two well established Supervised Learning techniques, Naïve Bayes and Maximum Entropy. Using the well known and publicly available Movie Review Dataset, the proposed hybrid system achieved higher accuracy and precision than Naïve Bayes (NB) and Maximum Entropy (ME).

Description

Keywords

Sentiment Analysis, Fuzzy Sets, Semantic Rules, Natural Language Processing, Computational Linguistic, SentiWordNet

Citation

Appel, O. et al. (2016) A Hybrid Approach to Sentiment Analysis with Benchmarking Results. Accepted for presentation at IEA/AIE-2016.

Rights

Research Institute

Institute of Artificial Intelligence (IAI)