互联网文本数据情感分析研究及在巴基斯坦YouTube用户评论中的应用

Mehwish Rani, Seemab Latif, Muhaammad Ali Tahir, R. Mumtaz
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引用次数: 2

摘要

随着社交媒体、电子商务和视频分享网站的出现,大量描述人们观点的文本数据正在产生。本文对其他网络用户、产品销售者和内容创作者都有很大的影响。基于文本分析的文本挖掘和情感检测近年来得到了很大的发展。情感分析是一种挖掘网络用户情感、评论和意见的方法。本文对文本情感分析技术进行了综述。情感分析应用于从巴基斯坦新闻视频中提取的评论。本文之前研究的不同机器学习算法已应用于该数据集。我们的结果表明,迁移学习可以有效地用于情感分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey of Sentiment Analysis of Internet Textual Data and Application to Pakistani YouTube User Comments
With the advent of social media, e-commerce and video sharing websites, a large amount of textual data depicting people’s opinions is being generated. This text has a great impact on other web users, product sellers and content creators. Text mining and emotion detection using text analysis has prospered a lot in recent years. Sentiment Analysis is the method of mining emotions, reviews and opinions of web users. In this paper, a survey of text Sentiment Analysis techniques is presented. Sentiment Analysis is applied to comments extracted from Pakistani news videos. Different machine learning algorithms previously surveyed in this paper have been applied to this dataset. Our results have shown that transfer learning can be effectively used for Sentiment Analysis.
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