A Domain-Specific Evaluation of the Performance of Selected Web-based Sentiment Analysis Platforms

Manuel O. Diaz Jr.
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引用次数: 1

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.
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选定的基于web的情感分析平台的特定领域性能评估
现在市场上有越来越多的情绪分析软件即服务(SA-SaaS)产品。情感分析的方法及其作为SA-SaaS的实现各不相同,并且确实无法确定哪种SA-SaaS使用哪种方法。对于潜在用户来说,SA-SaaS产品是黑盒。然而,黑盒可以使用一组标准输入和输出的比较来评估。使用现有研究中包含新闻标题情感极性的人类注释样本的测试数据集,本研究使用黑盒测试方法,比较了选定的流行和免费(或至少免费试用)SA-SaaS在情感分类的准确性、精密度、召回率和特异性方面的表现。英国伍尔弗汉普顿大学(University of Wolverhampton)开发的SentiStrength在所有指标上都表现一致。
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