Examining the Impact of Discretization Technique on Sentiment Analysis for the Greek Language

Nikolaos Spatiotis, I. Perikos, I. Mporas, M. Paraskevas
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引用次数: 3

Abstract

Nowadays, information, communication and interaction between people worldwide have been facilitated by the rapid development of technology and they are mainly achieved through the internet. Internet users are now new creators of information data and express their ideas, their opinions, their feelings and their attitudes about products and services rather than passive information recipients. Given the evolution of modern technological advances, such as the proliferation of mobile devices social networks and services is extending. User-generated content in social media constitutes a very meaningful information source and consists of opinions towards various events and services. In this paper, we present a methodology that aims to analyze Greek text and extract indicative info towards users’ opinions and attitudes. Specifically, we describe a supervised approach adopted that analyzes and classifies comments and reviews into the appropriate polarity category. Discretization techniques are also applied to improve the performance and the accuracy of classification procedures. Finally, we present an experimental evaluation that was designed and conducted and which revealed quite interesting findings.
考察离散化技术对希腊语情感分析的影响
如今,科技的飞速发展促进了世界各地人们之间的信息、交流和互动,这些主要是通过互联网实现的。互联网用户现在是信息数据的新创造者,他们表达自己的想法、观点、感受和对产品和服务的态度,而不是被动的信息接受者。鉴于现代技术的进步,如移动设备的扩散,社交网络和服务正在扩展。社交媒体中的用户生成内容是一个非常有意义的信息源,它包含了对各种事件和服务的意见。在本文中,我们提出了一种方法,旨在分析希腊文本并提取用户意见和态度的指示性信息。具体来说,我们描述了一种被采用的监督方法,该方法分析并将评论和评论分类到适当的极性类别中。离散化技术也被用于提高分类程序的性能和准确性。最后,我们提出了一个设计和实施的实验评估,并揭示了相当有趣的发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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