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A Survey of Opinion Mining in Arabic: A Comprehensive System Perspective Covering Challenges and Advances in Tools, Resources, Models, Applications, and Visualizations

机译:阿拉伯语的观点挖掘调查:涵盖工具,资源,模型,应用程序和可视化的挑战和进步的综合系统视角

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Opinion-mining or sentiment analysis continues to gain interest in industry and academics. While there has been significant progress in developing models for sentiment analysis, the field remains an active area of research for many languages across the world, and in particular for the Arabic language, which is the fifth most-spoken language and has become the fourth most-used language on the Internet. With the flurry of research activity in Arabic opinion mining, several researchers have provided surveys to capture advances in the field. While these surveys capture a wealth of important progress in the field, the fast pace of advances in machine learning and natural language processing (NLP) necessitates a continuous need for a more upto-date literature survey. The aim of this article is to provide a comprehensive literature survey for stateof-the-art advances in Arabic opinion mining. The survey goes beyond surveying previous works that were primarily focused on classification models. Instead, this article provides a comprehensive system perspective by covering advances in different aspects of an opinion-mining system, including advances in NLP software tools, lexical sentiment and corpora resources, classification models, and applications of opinion mining. It also presents future directions for opinion mining in Arabic. The survey also covers latest advances in the field, including deep learning advances in Arabic Opinion Mining. The article provides state-of-the-art information to help new or established researchers in the field as well as industry developers who aim to deploy an operational complete opinion-mining system. Key insights are captured at the end of each section for particular aspects of the opinion-mining system giving the reader a choice of focusing on particular aspects of interest.
机译:观点挖掘或情感分析继续引起行业和学术界的兴趣。尽管在开发情感分析模型方面已经取得了重大进展,但该领域仍然是世界上许多语言(尤其是阿拉伯语)研究的活跃领域,阿拉伯语是第五种最多使用的语言,已经成为第四大使用的语言。互联网上使用的语言。随着阿拉伯舆论挖掘研究活动的兴起,几位研究人员提供了调查以掌握该领域的进展。尽管这些调查在该领域取得了许多重要的进展,但是机器学习和自然语言处理(NLP)的飞速发展却使人们不断需要更新的文献调查。本文的目的是为阿拉伯意见挖掘的最新进展提供全面的文献综述。该调查超出了对以前主要关注分类模型的工作的调查范围。取而代之的是,本文通过涵盖意见挖掘系统各个方面的进展,包括NLP软件工具,词汇情感和语料库资源,分类模型以及意见挖掘的应用程序的进展,提供了一个全面的系统视角。它还为阿拉伯语的意见挖掘提出了未来的方向。该调查还涵盖了该领域的最新进展,包括阿拉伯语意见挖掘的深度学习进展。本文提供了最新信息,以帮助该领域的新手或老手研究人员以及旨在部署可操作的完整意见挖掘系统的行业开发商。在每个部分的末尾都有针对观点挖掘系统特定方面的关键见解,使读者可以选择关注感兴趣的特定方面。

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