DocumentCode
163441
Title
Sentiment Analysis in Arabic tweets
Author
Duwairi, Rehab M. ; Marji, Raed ; Sha´ban, Narmeen ; Rushaidat, Sally
Author_Institution
Dept. of Comput. Inf. Syst., Jordan Univ. of Sci. & Technol., Irbid, Jordan
fYear
2014
fDate
1-3 April 2014
Firstpage
1
Lastpage
6
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
data analysis; natural language processing; social networking (online); Arabic dialects; Arabic sentiment analysis; Arabic tweets; Arabizi; Twitter comments analysis; crowdsourcing; emoticons; social media platforms; Accuracy; Dictionaries; Internet; Media; Niobium; Sentiment analysis; Support vector machines; Arabic Sentiment Analysis; Crowdsourcing; Data Analytics; Opinion Mining; Supervised Learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Communication Systems (ICICS), 2014 5th International Conference on
Conference_Location
Irbid
Print_ISBN
978-1-4799-3022-7
Type
conf
DOI
10.1109/IACS.2014.6841964
Filename
6841964
Link To Document