Kurdish Language Sentiment Analysis: Problems and Challenges

Q4 Mathematics
Miran Hama Saeed Mohammed Amin, Omar Al-Rassam, Zhenar Shaho Faeq
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引用次数: 1

Abstract

The increasing usage of blogs, social networks, and forums for sharing opinions on a certain topic has created vast amounts of internet data. Therefore, Sentiment Analysis has gained great popularity among researchers and industry for analyzing the polarity of users' opinions. In recent years, Sentiment Analysis has been applied to various languages using machine learning-approach, corpus-based approach, and deep learning techniques since it is beneficial for creating an effective recommender system. The Kurdish Language is an Indo-European language, one of the official languages in Iraq, and it is also widely used in Turkey, Iran, and Syria. Although the importance of this Language is spoken by over 40 million people, to the best of our knowledge, no research has been done regarding the challenges and problems of Kurdish sentiment analysis. Our research aims to highlight the latest studies and examine the most critical challenges of applying sentiment analysis approaches to the Kurdish Language. The study includes determining each challenge in each step of sentiment analysis processing in the Kurdish Language. In addition, our proposed methodology that could help address most of these challenges is implementing a hybrid approach by combining machine learning and lexicon-based approaches to improve the proficiency of sentiment classification in the Kurdish Language.
库尔德语言情感分析:问题与挑战
越来越多的人使用博客、社交网络和论坛来分享对某个主题的看法,这产生了大量的互联网数据。因此,情感分析在研究人员和行业中受到了广泛的欢迎,用于分析用户意见的极性。近年来,情感分析已经通过机器学习方法、基于语料库的方法和深度学习技术应用于各种语言,因为它有利于创建有效的推荐系统。库尔德语是一种印欧语,是伊拉克的官方语言之一,在土耳其、伊朗和叙利亚也被广泛使用。尽管有超过4000万人使用这种语言,但据我们所知,还没有关于库尔德情绪分析的挑战和问题的研究。我们的研究旨在强调最新的研究,并研究将情感分析方法应用于库尔德语的最关键挑战。该研究包括确定库尔德语情感分析处理的每个步骤中的每个挑战。此外,我们提出的方法可以帮助解决大多数这些挑战,通过结合机器学习和基于词典的方法来实现混合方法,以提高库尔德语情感分类的熟练程度。
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来源期刊
Philippine Statistician
Philippine Statistician Mathematics-Statistics and Probability
CiteScore
0.50
自引率
0.00%
发文量
92
期刊介绍: The Journal aims to provide a media for the dissemination of research by statisticians and researchers using statistical method in resolving their research problems. While a broad spectrum of topics will be entertained, those with original contribution to the statistical science or those that illustrates novel applications of statistics in solving real-life problems will be prioritized. The scope includes, but is not limited to the following topics:  Official Statistics  Computational Statistics  Simulation Studies  Mathematical Statistics  Survey Sampling  Statistics Education  Time Series Analysis  Biostatistics  Nonparametric Methods  Experimental Designs and Analysis  Econometric Theory and Applications  Other Applications
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