NileTMRG at SemEval-2016 Task 7: Deriving prior polarities for Arabic sentiment terms

SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings

Volumn , Issue , 2016, Pages 486-490

  El Beltagy, Samhaa R ^a  

^a NILE UNIVERSITY   (Egypt)

Author keywords

[No Author keywords available]

Indexed keywords

SEMANTICS;

INTENSITY SCORES; MUTUAL INFORMATIONS; POINT WISE; STRENGTH VALUES;

SOCIAL NETWORKING (ONLINE);

EID: 85035745969     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.18653/v1/s16-1079     Document Type: Conference Paper

References (20)

1. Apache, 2011. Lucene. Available at: http://lucene.apache.org/.
2. Astudillo, R. F. et al., 2015. INESC-ID: A Regression Model for Large Scale Twitter Sentiment Lexicon Induction. In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015). pp. 613-618. Available at: http://alt.qcri.org/SemEval2015/cdrom/pdf/SemEv al102.pdf.
3. Baccianella, S., Esuli, A. & Sebastiani, F., 2010. SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10). pp. 2200-2204.
4. Bouma, G., 2009. Normalized (Pointwise) Mutual Information in Collocation Extraction. In the Biennial GSCL Conference. pp. 31-40.
5. El-Beltagy, S. R. et al., 2016. Combining Lexical Features and a Supervised Learning Approach for Arabic Sentiment Analysis. In CICLing 2016 - submitted. Konya, Turkey.
6. El-Beltagy, S. R., 2016. NileULex: A Phrase and Word Level Sentiment Lexicon for Egyptian and Modern Standard Arabic. In to appear in proceedings of LREC 2016. Portorož, Slovenia.
7. El-Beltagy, S. R. & Ali, A., 2013. Open Issues in the Sentiment Analysis of Arabic Social Media: A Case Study. In Proceedings of 9th the International Conference on Innovations and Information Technology (IIT2013). Al Ain, UAE.
8. El-Beltagy, S. R. & Rafea, A., 2011. An Accuracy Enhanced Light Stemmer for Arabic Text. ACM Transactions on Speech and Language Processing, 7(2), pp. 2-23.
9. Eskander, R. & Rambow, O., 2015. SLSA: A Sentiment Lexicon for Standard Arabic. Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, (September), pp. 2545-2550. Available at: http://aclweb.org/anthology/D15-1304.
10. Hamdan, H., Bellot, P. & Bechet, F., 2015. lsislif: Feature extraction and label weighting for sentiment analysis in twitter. In Proceedings of the 9th International Workshop on Semantic Evaluation. pp. 568-573.
11. Khalil, T. et al., 2015. Which configuration works best? An experimental study on Supervised Arabic Twitter Sentiment Analysis. In Proceedings of the First Conference on Arabic Computational Liguistics (ACLing 2015), co-located with CICLing 2015. Cairo, Egypt, pp. 86-93.
12. Kiritchenko, S., Zhu, X. & Mohammad, S., 2014. Sentiment Analysis of Short Informal Texts. Journal of Artificial Intelligence Research, 50, pp. 723-762.
13. Leskovec, J., Rajaraman, A. & Ullman, J. D., 2014. Mining of Massive Datasets 2 edition., Cambridge, UK: Cambridge University Press. Available at: http://ebooks.cambridge.org/ref/id/CBO97811390 58452.
14. Liu, B., 2010. Sentiment Analysis and Subjectivity. In N. I. and F. J. Damerau, ed. Handbook of Natural Language Processing, Second Edition.
15. Mohammad, S. & Turney, P., 2013. Crowdsourcing a Word-Emotion Association Lexicon. Computational Intelligence, 29(3), pp. 436-465.
16. Mohammad, S. M., Kiritchenko, S. & Zhu, X., 2013. NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets. In Proceedings of the seventh international workshop on Semantic Evaluation Exercises (SemEval-2013). Atlanta, Georgia, USA.
17. Rennie, J. D. M. et al., 2003. Tackling the Poor Assumptions of Naive Bayes Text Classifiers. Proceedings of the Twentieth International Conference on Machine Learning (ICML)-2003), 20(1973), pp. 616-623.
18. Rosenthal, S. et al., 2015. SemEval-2015 Task 10: Sentiment Analysis in Twitter. In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015). pp. 451-463. Available at: http://alt.qcri.org/SemEval2015/cdrom/pdf/SemEv al078.pdf.
19. Twitter, 2016. Twitter Search API. Available at: https://dev. twitter.com/rest/public/search.
20. Wilson, T., Wiebe, J. & Hoffmann, P., 2005. Recognizing contextual polarity in phrase-level sentiment analysis. In Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP). Vancouver, Canada, pp. 347-354.