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Smart city article details
| Title | Sentiment Analysis Of Arabic Tweets In Smart Cities: A Review Of Saudi Dialect |
|---|---|
| ID_Doc | 48458 |
| Authors | Alotaibi S.; Mehmood R.; Katib I. |
| Year | 2019 |
| Published | 2019 4th International Conference on Fog and Mobile Edge Computing, FMEC 2019 |
| DOI | http://dx.doi.org/10.1109/FMEC.2019.8795331 |
| Abstract | 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. © 2019 IEEE. |
| Author Keywords | Arabic Dialects; Arabic Language; Big Data Analytics; Corpus; Machine Learning; Saudi Dialects; Sentiment Analysis; Smart Cities; Twitter |
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