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Sentiment Analysis on Turkish Social Media Shares through Lexicon Based Approach

机译:基于词汇的方法对土耳其社交媒体份额的情感分析

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Social media platforms provide an environment that allows users to see the shares made up to that time on a particular subject or situation. Reading and analysing millions of comments made on a given subject or situation is a costly process that takes considerable amount of time. For this reason, the development of applications that automatically perform such analyses has become a necessity nowadays when the use of social media is increasing rapidly. In this study, messages written in Turkish that had been shared on Twitter, which is one of the most used social media platforms, were analysed with the help of lexicon-based method which is one of the approaches used in sentiment analysis after being passed through various pre-processing stages. As a result of this sentiment analysis, according to the sentimental densities they carry, they have been classified in three categories namely positive, negative, or neutral. As a conclusion of the studies performed, the classification and sentiment analysis process was performed with a success rate of approximately 80%.
机译:社交媒体平台提供了一种环境,使用户可以查看到该时间为止在特定主题或情况下所占的份额。阅读和分析针对给定主题或情况作出的数百万条评论是一个昂贵的过程,需要花费大量时间。因此,在社交媒体的使用迅速增长的今天,开发自动执行此类分析的应用程序已成为必需。在这项研究中,使用基于词典的方法分析了土耳其语写的消息,该消息已在Twitter上被共享,Twitter是最常用的社交媒体平台之一,该方法是情感分析通过后的一种方法各种预处理阶段。情感分析的结果是,根据它们所携带的情感密度,将其分为积极,消极或中立三个类别。作为所进行研究的结论,分类和情感分析过程的成功率约为80%。

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