Sentiment Analysis of Arabic Tweets in Smart Cities: A Review of Saudi Dialect

被引:0
|
作者
Alotaibi, Shoayee [1 ]
Mehmood, Rashid [2 ]
Katib, Iyad [1 ]
机构
[1] King Abdulaziz Univ, Fac Comp & Informat Technol, Comp Sci Dept, Jeddah, Saudi Arabia
[2] King Abdulaziz Univ, High Performance Comp Ctr, Jeddah, Saudi Arabia
关键词
Arabic Language; Arabic Dialects; Corpus; Machine Learning; Smart Cities; Saudi Dialects; Sentiment Analysis; Twitter; Big Data Analytics; BIG DATA; TRANSPORT; ALGORITHMS; LOGISTICS; CORPUS;
D O I
10.1109/fmec.2019.8795331
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Social media including Twitter have transformed our societies and has become an important pulse of smart societies by sensing the information about the people and their experiences across space and time around the living spaces. This has allowed connecting with people, sensing their feelings and behaviors, and measuring the performance of various city systems such as healthcare and transport. The sentiment analysis of social media is a key step in this process. As of January 2019, Saudi Arabia had the fourth highest number of Twitter users in the world, after the US, Japan, and the UK. However, the works done on sentiment analysis in the Arabic language are limited in their scope and depth. Moreover, little is available in the literature on sentiment analysis in the Arabic and Saudi dialects. This paper aims to provide a resource on the sentiment analysis in the Arabic and Saudi dialects. It reviews the relevant tools and techniques considering their accuracy. We hope that this paper will be a useful guide for the researchers who are interested in the sentiment analysis of the Arabic and the Saudi dialects.
引用
收藏
页码:330 / 335
页数:6
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