publication . Other literature type . Article . 2017

Developing Resources For Sentiment Analysis Of Informal Arabic Text In Social Media

Itani, Maher; Roast, Chris; Al-Khayatt, Samir;
  • Published: 01 Jan 2017
  • Publisher: Elsevier BV
  • Country: United Kingdom
Natural Language Processing (NLP) applications such as text categorization, machine translation, sentiment analysis, etc., need annotated corpora and lexicons to check quality and performance. This paper describes the development of resources for sentiment analysis specifically for Arabic text in social media. A distinctive feature of the corpora and lexicons developed are that they are determined from informal Arabic that does not conform to grammatical or spelling standards. We refer to Arabic social media content of this sort as Dialectal Arabic (DA) - informal Arabic originating from and potentially mixing a range of different individual dialects. The paper ...
free text keywords: Spelling, Distinctive feature, Natural language processing, computer.software_genre, computer, Sentiment analysis, sort, Computer science, Text categorization, Social media, Artificial intelligence, business.industry, business, Arabic, language.human_language, language, Machine translation
Related Organizations
49 references, page 1 of 4

[1] El-Halees, A., 2011. Arabic opinion mining using combined classification approach.

[2] Jin, X., Li, Y., Mah, T. and Tong, J., 2007, August. Sensitive webpage classification for content advertising. In Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising (28-33). ACM.

[3] Mishne, G. and Glance, N.S., 2006, March. Predicting Movie Sales from Blogger Sentiment. In AAAI spring symposium: computational approaches to analyzing weblogs (155-158).

[4] Shikalgar, N.R. and Badgujar, D., 2013. Online Review Mining for forecasting sales. International Journal for research in Engineering & Technologies (IJRET) December. [OpenAIRE]

[5] Tatemura, J., 2000, January. Virtual reviewers for collaborative exploration of movie reviews. In Proceedings of the 5th international conference on Intelligent user interfaces ( 272-275). ACM.

[6] Somasundaran, S., Wilson, T., Wiebe, J. and Stoyanov, V., 2007, March. QA with Attitude: Exploiting Opinion Type Analysis for Improving Question Answering in On-line Discussions and the News. In ICWSM.

[7] Stoyanov, V., Cardie, C. and Wiebe, J., 2005, October. Multi-perspective question answering using the OpQA corpus. In Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing ( 923-930). Association for Computational Linguistics.

[8] Bollen, J., Mao, H. and Zeng, X., 2011. Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8. [OpenAIRE]

[9] Izwaini, S., 2003, March. Building specialised corpora for translation studies. In Workshop on Multilingual Corpora: Linguistic Requirements and Technical Perspectives, Corpus Linguistics.

[10] The Arabic Language. 2013. [Online] Available at [Accessed 17 July 2016]

[12] Official Languages, Un.Org, United Nations, 2016. [Online] Available at: [Accessed 17 July 2016]

[13] What is Spoken Arabic / the Arabic Dialects?, 2015, [Online] Available at: [Accessed 17 July 2016]

[14] Houngbo, H. and Mercer, R.E., 2014, June. An automated method to build a corpus of rhetorically-classified sentences in biomedical texts. In Proceedings of the First Workshop on Argumentation Mining (19-23).

[15] Lita, L.V., Schlaikjer, A.H., Hong, W. and Nyberg, E., 2005, July. Qualitative dimensions in question answering: Extending the definitional QA task. In PROCEEDINGS OF THE NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (Vol. 20, No. 4, 1616). Menlo Park, CA; Cambridge, MA; London; AAAI Press; MIT Press; 1999.

[16] Carlson, L., Marcu, D. and Okurowski, M.E., 2003. Building a discourse-tagged corpus in the framework of rhetorical structure theory. In Current and new directions in discourse and dialogue (85-112). Springer Netherlands.

49 references, page 1 of 4
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue
publication . Other literature type . Article . 2017

Developing Resources For Sentiment Analysis Of Informal Arabic Text In Social Media

Itani, Maher; Roast, Chris; Al-Khayatt, Samir;