Abstract

Social media platforms such as blogs, social networking sites, content communities and virtual worlds are tremendously becoming one of the most powerful sources for news, markets, industries, and much more. They are a wide platform full of thoughts, emotions, reviews and feedback, which can be used in many aspects. Despite these great avails, and with the increasingly enormous number of Arabic users on the internet, little research has tied these two together in a high and accurate professional manner [1]. This paper deals with Arabic Sentiment Analysis. We developed a framework that makes it possible to analyze Twitter comments or "Tweets" as having positive, negative or neutral sentiments. This can be applied in a wide range of applications ranging from politics to marketing. This framework has many novel aspects such as handling Arabic dialects, Arabizi and emoticons. Also, crowdsourcing was utilized to collect a large dataset of tweets.

Keywords:
Crowdsourcing Arabic Sentiment analysis Computer science Social media The Internet Data science World Wide Web Natural language processing Linguistics

Metrics

146
Cited By
20.77
FWCI (Field Weighted Citation Impact)
8
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Sentiment Analysis and Opinion Mining
Physical Sciences →  Computer Science →  Artificial Intelligence
Spam and Phishing Detection
Physical Sciences →  Computer Science →  Information Systems
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence

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