在物联网应用中使用阿拉伯语COVID-19推文分析

F. Alderazi, A. Algosaibi, M. Alabdullatif
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引用次数: 0

摘要

社交媒体平台已经成为组织和个人发布新闻和表达想法或感受的最强大工具之一。随着沙特阿拉伯互联网用户数量的不断增加,分析阿拉伯语帖子的必要性也越来越高。自2019年COVID-19出现以来,各国政府采取了新的隔离措施来应对病毒的传播,而经济和企业则在计算成本。考虑到快速及时的数据分析和共享对政策行动的重要性,人工智能(AI)在促进冠状病毒大流行期间科学家和决策者之间的意见和信息交流方面发挥了至关重要的作用,他们将继续这样做。这项工作挖掘了这些与内容相关的推文,看看人们的感受和表达是如何变化的。该分析结果可与多种物联网技术集成使用,以减少covid-19的影响,并推动该领域的新决策。为此,我们提出了一个机器学习(ML)模型,该模型可以对现代标准阿拉伯语(MSA)推文的情感和主题进行分类,并获得高精度的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Use of Arabic Language COVID-19 Tweets Analysis in IoT Applications
Social media platforms have become one of the most powerful tools for organizations and individuals to publish news and express thoughts or feelings. With the increasingly enormous number of internet users in Saudi Arabia, the need raised to analyze Arabic posts. Since the emergence of COVID-19 in the latest 2019, it lefts economies and businesses counting the cost while governments fight the spread of the virus with new compartmentalization measures. Keeping in view the importance of quick and timely data analysis and sharing for policy actions, Artificial intelligence (AI) has played a crucial role in facilitating the exchange of views and information between scientists and decision-makers during the Coronavirus pandemic, and they continue to do so. This work mined to these content-related tweets to see how people’s feelings and expressions are changing. The results of this analysis can be used with integration with several IoT technologies to reduce the impact of covid-19 and drive new decisions in this field. For this goal, we proposed a Machine Learning (ML) models that can classify both of the sentiment and topic of Modern Standard Arabic (MSA) tweets and achieve high accuracy results.
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