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DOI: 10.14569/IJACSA.2017.080237
PDF

Sentiment Analysis Challenges of Informal Arabic Language

Author 1: Salihah AlOtaibi
Author 2: Muhammad Badruddin Khan

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 2, 2017.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Recently, there are wide numbers of users that use the social network like Twitter, Facebook, MySpace to share various kinds of resources, express their opinions, thoughts, messages in real time. Thus, increase the amount of electronic content that generated by users. Sentiment analysis becomes a very interesting topic in research community. Thereby, we need to give more attention to Arabic sentiment analysis. This paper discusses the challenges and obstacles when analyze the sentiment analysis of informal Arabic, the social media. The most of recent research sentiment analysis conduct for English text. Also, when the research works in Arabic sentiment analysis, they focus in formal Arabic. However, most of social media network use the informal Arabic (colloquial) such as Twitter and YouTube website. This paper investigates the problems and the challenges to identify sentiment in informal Arabic language which is mostly used when users express their opinions and feelings in context of twitter and YouTube Arabic content.

Keywords: Informal Arabic; Sentiment analysis; Opinion Mining (OM) ; Twitter; YouTube

Salihah AlOtaibi and Muhammad Badruddin Khan, “Sentiment Analysis Challenges of Informal Arabic Language” International Journal of Advanced Computer Science and Applications(IJACSA), 8(2), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080237

@article{AlOtaibi2017,
title = {Sentiment Analysis Challenges of Informal Arabic Language},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080237},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080237},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {2},
author = {Salihah AlOtaibi and Muhammad Badruddin Khan}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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