Survey on Arabic Sentiment Analysis in Twitter
Commenced in January 2007
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Edition: International
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Survey on Arabic Sentiment Analysis in Twitter

Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

Abstract:

Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: Big Data, Social Networks, Sentiment Analysis.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1099604

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References:


[1] J. Gantz and D. Reinsel, "Digital Universe Study: Extracting Value from Chaos," EMC2, June 2011. (Online). Available: Internet: http://www.emc.com/leadership/programs/digital-universe.htm (Accessed 6 Nov 2014).
[2] "The 2011 IDC Digital Universe study sponsored by EMC," (Online). Available: http://www.emc.com/collateral/about/news/idc-emc-digital-universe-2011-infographic.pdf(Accessed 6 Nov 2014).
[3] S. Sagiroglu and a. D.Sinanc. "Big data: A review," in Proc. CTS, 2013, pp. 42 – 47.
[4] "Social Media Usage in Middle East – Statistics and Trends (Infographic)," Go-Gulf, 4 Jun 2013. (Online). Available: http://www.go-gulf.com/blog/social-media-middle-east (Accessed 6 Nov 2014).
[5] B. Liu. (2012, Apr 22). Sentiment Analysis and Opinion Mining, (1st edition). (On-line). Available: http://www.cs.uic.edu/~liub/FBS/SentimentAnalysis-and-OpinionMining.pdf (Des 22, 2014]).
[6] "About," Twitter, (Online). Available: https://about.twitter.com/what-is-twitter. (Accessed 6 Nov 2014).
[7] J. Akaichi. "Social Networks' Facebook' Statutes Updates Mining for Sentiment Classification," in Porc. SOCIALCOM, 2013, pp. 886 - 891.
[8] R. Khasawneh, H. Wahsheh, M. Al Kabi and I. Aismadi. "Sentiment analysis of arabic social media content: a comparative study," in Porc. ICITST, 2013, pp. 101 - 106.
[9] M. Itani, B. A. U. B. L. Math. &Comput. Sci. Dept., L. Hamandi, R. Zantout and I. Elkabani. "Classifying sentiment in arabic social networks: Naïve search versus Naïve bayes," in Porc. ACTEA, 2012, pp. 192 - 197.
[10] A. Mountassir, M. 5. U. R. M. ALBIRONI Res. Team, H. Benbrahim and I. Berrada. "Some methods to address the problem of unbalanced sentiment classification in an arabic context," in Porc. CIST, 2012, pp. 43 - 48.
[11] M. Al-Kabi, Z. J. Zarqa Univ., N. Abdulla and M. Al-Ayyoub. "An analytical study of Arabic sentiments: Maktoob case study," in Porc. ICITST, 2013, pp. 89 - 94.
[12] J. Varlack. "What are Blogs?," MedNews Blog, 2 March 2009 . (Online). Available: http://www.mednet-tech.com/newsletter/blogs/what-are-blogs. (Accessed 6 Nov 2014).
[13] A. Shoukry and a. A. Rafea. "Sentence Level Arabic Sentiment Analysis," in Proc. CTS, 2012, pp. 546 – 550.
[14] N. Abdulla, N. Ahmed, M. Shehab and a. M. Al-Ayyoub. "Arabic Sentiment Analysis: Lexicon-Based and Corpus-Based," in Proc. AEECT, 2013, pp. 1 – 6.
[15] S. Ahmed and G. Qadah. "Key Issues in Conducting Sentiment Analysis on Arabic Social Media Text," in Porc. IIT, 2013, pp. 72 – 77.
[16] S. El-Beltagy and A. Ali. "Open Issues in the Sentiment Analysis of Arabic," in Porc. IIT, 2013, pp. 215-220.
[17] M. Abdul-Mageed, S. K¨ubler and a. M. Diab. "SAMAR: A System for Subjectivity and Sentiment Analysis of Arabic Social Media," in Proc. WASSA, 2012, pp. 19-28.
[18] J. Salamah and a. A. Elkhlifi. "Microblogging Opinion Mining Approach for Kuwaiti Dialect," in Proc. ICCTIM, Dubai, 2014.
[19] S. Al-Osaimi and a. K. Badruddin. "Role of Emotion icons in Sentiment classification of Arabic Tweets," in Porc. MEDES '14, 2014, pp.167-171.
[20] R. Duwairi, R. Marji, N. Sha'ban and S. Rushaidat. "Sentiment Analysis in Arabic Tweets," in Porc. ICICS, 2014, pp. 1 - 6.
[21] L. Albraheem and a. H. Al-Khalifa. "Exploring the problems of Sentiment Analysis in Informal," in Proc. IIWAS '12, 2012, pp. 415-418.