CFP last date
20 June 2024
Call for Paper
July Edition
IJCA solicits high quality original research papers for the upcoming July edition of the journal. The last date of research paper submission is 20 June 2024

Submit your paper
Know more
Reseach Article

Orthogonal Processing for Measuring the Tonality of Egyptian Microblogs

by Madeeh Nayer El-gedawy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 7
Year of Publication: 2014
Authors: Madeeh Nayer El-gedawy
10.5120/15220-3730

Madeeh Nayer El-gedawy . Orthogonal Processing for Measuring the Tonality of Egyptian Microblogs. International Journal of Computer Applications. 87, 7 ( February 2014), 20-25. DOI=10.5120/15220-3730

@article{ 10.5120/15220-3730,
author = { Madeeh Nayer El-gedawy },
title = { Orthogonal Processing for Measuring the Tonality of Egyptian Microblogs },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 7 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 20-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number7/15220-3730/ },
doi = { 10.5120/15220-3730 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:05:18.349771+05:30
%A Madeeh Nayer El-gedawy
%T Orthogonal Processing for Measuring the Tonality of Egyptian Microblogs
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 7
%P 20-25
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Subjectivity and Sentiment Analysis (SSA) research in Arabic is still in its beginning phases regarding the research done in English on different granularities (sentence and document levels). In this paper, a simple system is proposed to perform sentiment analysis (or polarity detection) using an aggressive stemmer in the preprocessing phase followed by a Fuzzy classifier. The main focus of this paper is optimizing the preprocessing tasks for better tonality detection performance. Twitter is used as the data source because it is considered one of the hugest online dialectal Arabic microblogs repositories.

References
  1. Bing Liu. Sentiment analysis and subjectivity (2010). Handbook of Natural Langauge Processing, pages 627-666.
  2. Johansson, Richard (2013). "Relational Features in Fine-Grained Opinion Analysis". Computational linguistics, Association for Computational Linguistics (0891-2017), 39 (3), page 473.
  3. Muhammad Abdul-Mageed, Mona Diab, and Mohammed Korayem (2011). Subjectivity and sentiment analysis of modern standard arabic. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 587–591.
  4. Hasan Muaidi and Rasha Al-tarawneh (2012). Towards Arabic Spell-Checker Based on N-Grams Scores. International Journal of Computer Applications 53(3), pages:12-16,. Published by Foundation of Computer Science, New York, USA.
  5. Vipperla, Ravichander,Frankel, Joe,Kin (2012). Direct posterior confidence for out-of-vocabulary spoken term detection, ACM Transactions on Information Systems (TOIS), volume 30, number 3.
  6. emalatha, G. P Saradhi Varma ,A. Govardhan (2012). Preprocessing the Informal Text for efficient Sentiment Analysis, Preprocessing the Informal Text for efficient Sentiment Analysis, volume 1, number2.
  7. Emma Haddia,Xiaohui Liua,Yong Shib (2013). The Role of Text Pre-processing in Sentiment Analysis, Procedia Computer Science, Volume 17, pages 26–32.
  8. Isa Maks, Piek Vossen (2012). A lexicon model for deep sentiment analysis and opinion mining applications, Decision Support Systems, Volume 53, number 4, pages 680-688.
  9. Ahmed Mourad, Kareem Darwish (2013). Subjectivity and Sentiment Analysis of Modern Standard Arabic and Arabic Microblogs, Proceedings of the 4th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 55–64, Atlanta, Georgia.
  10. Alexander Pak and Patrick Paroubek (2010). Twitter as a corpus for sentiment analysis and opinion mining, In Proceedings of LREC, volume 2010.
  11. M. Diab. 2009. Second Generation Tools (AMIRA 2. 0): Fast and Robust Tokenization, POS tagging, and Base Phrase Chunking. Proceedings of the Second International Conference on Arabic Language Resources and Tools, 2009.
  12. S. Khoja, R. Garside (1999). Stemming Arabic text, Tech. rep. Computing Department, Lancaster University, Lancaster, U. K.
  13. Mohammed A. Otair (2013). Comparative analysis of Arabic stemming algorithms, International Journal of Managing Information Technology, volume 5.
  14. Samhaa R. El-Beltagy, Ahmed Rafea (2011). An accuracy-enhanced light stemmer for arabic text , ACMTransactions on Speech and Language Processing (TSLP) , Volume 7 number 2 .
  15. Goweder, A. , Poesio, M. , De Roeck, A. , Reynolds, J. : Identifying broken plurals in unvowelised Arabic text. In: EMNLP 2004, Barcelona, Spain (2004).
  16. K. Darwish, H. Hassan, O. Emam (2005). Examining the Effect of Improved Context Sensitive Morphology on Arabic Information Retrieval. CASL workshop in ACL.
  17. R. AI-Shalabi, G. Kannan, and H. AI-Serhan (2003). "New Approach for extracting Arabic roots". In Proc of 2003 International Arab conference on Information Technology, Alexandria, Pages: 42-59.
  18. Zhou Yao, Cao Ze-wen (2011). "Research on the Construction and Filter Method of Stop-word List in Text Preprocessing". Proceedings of the 2011 Fourth International Conference on Intelligent Computation Technology and Automation, Volume 1.
  19. Ronen Feldman, James Sanger (2006). "Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data". Cambridge University Press, NY, USA.
  20. Mehdi Khosrow-Pour (2008). "Encyclopedia of Information Science and Technology, 2 edition". Information Science Reference - Imprint of: IGI Publishing Hershey, PA.
  21. Amira Shoukry (2013). Arabic Sentence-level sentiment analysis, A Thesis Submitted to The Department of Computer Science and Engineering, AUC, Cairo, Egypt.
  22. Mona Diab, Nezar Habash (2009). Arabic Dialect processing. MEDAR 2009, Cairo, Egypt.
  23. Amira Shoukry, Ahmed Rafea (2012). Preprocessing Egyptian Dialect Tweets for Sentiment Mining, In proceeding of: Fourth Workshop on Computational Approaches to Arabic, AMTA.
  24. Karim Darwish, Walid Magdy, Ahmed Mourad (2012). Language processing for arabic microblog retrieval, in proceedings of the 21st ACM international conference on Information and knowledge management, pages 2427-2430 ACM New York, USA.
  25. Khaled Shaalan, Hitham Bakr, Ibrahim Ziedan (2007). Transferring Egyptian Colloquial Dialect into Modern Standard Arabic, in international conference on recent advances in Natural Language Processing (RANLP), pages 525-529.
  26. Feng Zou, Fu Lee Wang, Xiaotie Deng, Song Han, Lu Sheng Wang (2006). "Automatic construction of Chinese stop word list". Proceedings of the 5th WSEAS international conference on applied computer science, Pages: 1009-1014.
  27. A. Alajmi, E. M. Saad, R. R. Darwish (2012). "Toward an ARABIC Stop-Words List Generation". International Journal of Computer Applications (0975 – 8887), Volume 46, Number 8.
  28. Madeeh Nayer El-gedawy (2013). Using Fuzzifiers to solve Word Sense Ambiguation in Arabic Language, International Journal of Computer Applications 79(2):1-8, New York, USA.
  29. William H. Press, Saul A. Teukolsky, William T. Vetterling, Brian P. Flannery (2007). "Numerical Recipes 3rd Edition: The Art of Scientific Computing, 3 edition". Cambridge University Press, New York, USA.
Index Terms

Computer Science
Information Sciences

Keywords

Sentiment – aggressive - stemmer – normalization – stops word removal – Fuzziers.