A DOMAIN-SPECIFIC EVALUATION OF THE PERFORMANCE OF SELECTED WEB-BASED SENTIMENT ANALYSIS PLATFORMS

Authors

DOI:

https://doi.org/10.15282/ijsecs.9.1.2023.1.0105

Keywords:

Sentiment analysis, Sentiment polarity, Polarity identification, Analysis-as-a-service, Text classification

Abstract

There is now an increasing number of sentiment analysis software-as-a-service (SA-SaaS) offerings in the market. Approaches to sentiment analysis and their implementation as SA-SaaS vary, and there really is no sure way of knowing what SA-SaaS uses which approach. For potential users, SA-SaaS products are black boxes. Black boxes, however, can be evaluated using a set of standard input and a comparison of the output. Using a test data set drawn from human annotated samples in existing studies covering sentiment polarity of news headlines, this study compares the performance of selected popular and free (or at least free-to-try) SA-SaaS in terms of the accuracy, precision, recall and specificity of the sentiment classification using the black box testing methodology. SentiStrength, developed at the University of Wolverhampton in the UK, emerged as consistent performer across all metrics.

Published

2023-01-03

How to Cite

Diaz Jr., M. O. (2023). A DOMAIN-SPECIFIC EVALUATION OF THE PERFORMANCE OF SELECTED WEB-BASED SENTIMENT ANALYSIS PLATFORMS. International Journal of Software Engineering and Computer Systems, 9(1), 01–09. https://doi.org/10.15282/ijsecs.9.1.2023.1.0105