Arabic Tweets Sentimental Analysis Using Machine Learning-Reference-Cited by-同舟云学术

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Arabic Tweets Sentimental Analysis Using Machine Learning

Published:2017 Issue: Volume: Page:602-610
ISSN:0302-9743
Container-title:Advances in Artificial Intelligence: From Theory to Practice
language:
Short-container-title:

Author:

Alomari Khaled Mohammad^ORCID,ElSherif Hatem M.^ORCID,Shaalan Khaled^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-60042-0_66

Reference21 articles.

1. INternet World Stats: Internet World Users by Language. Top 10 Languages. http://www.internetworldstats.com/stats7.htm

2. Al-Kabi, M., Al-Qudah, N.M., Alsmadi, I., Dabour, M., Wahsheh, H. (eds.): Arabic/English Sentiment Analysis: An Empirical Study (2013)

3. Agarwal, B., Mittal, N.: Prominent Feature Extraction for Sentiment Analysis. Springer, Cham (2016)

4. Farghaly, A., Shaalan, K.: Arabic natural language processing: challenges and solutions. TALIP 8, 1–22 (2009)

5. Ray, S.K., Shaalan, K.: A review and future perspectives of arabic question answering systems. IEEE Trans. Knowl. Data Eng. 28, 3169–3190 (2016)

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