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.

Full Text
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