J. Baldridge, The opennlp project, 2005.

F. Barbieri, M. Ballesteros, and H. Saggion, , 2017.

S. Chaffar and D. Inkpen, Using a heterogeneous dataset for emotion analysis in text, Canadian Conference on Artificial Intelligence, pp.62-67, 2011.

B. Eisner, T. Rocktäschel, I. Augenstein, M. Bo?, and S. Riedel, emoji2vec: Learning Emoji Representations from their Description, 2016.
DOI : 10.18653/v1/w16-6208

URL : https://doi.org/10.18653/v1/w16-6208

H. Hamdan, P. Bellot, and F. Bechet, Sentiment lexiconbased features for sentiment analysis in short text, Proceeding of the 16th International Conference on Intelligent Text Processing and Computational Linguistics, 2015.

S. Hochreiter and J. Schmidhuber, Long Short-Term Memory, Neural Comput, vol.9, pp.1735-1780, 1997.

S. Huang, W. Peng, J. Li, and D. Lee, Sentiment and topic analysis on social media: a multi-task multi-label classification approach, Proceedings of the 5th annual acm web science conference, pp.172-181, 2013.
DOI : 10.1145/2464464.2464512

C. Kelly, Do you know what I mean >:(: A linguistic study of the understanding of emoticons and emojis in text messages. Master's thesis, 2015.

P. K. Novak and J. Smailovic, Borut Sluban, and Igor Mozetic, Sentiment of Emojis, vol.10, p.12, 2015.

B. Lauser and A. Hotho, Automatic multi-label subject indexing in a multilingual environment, International Conference on Theory and Practice of Digital Libraries, pp.140-151, 2003.
DOI : 10.1007/978-3-540-45175-4_14

URL : http://www.aifb.uni-karlsruhe.de/WBS/aho/pub/lauserhothoecdl03.pdf

A. Lenhart, A. Smith, M. Anderson, M. Duggan, and A. Perrin, Teens, technology and friendships, 2015.

W. Li and H. Xu, Text-based emotion classification using emotion cause extraction, Expert Systems with Applications, vol.41, pp.1742-1749, 2014.
DOI : 10.1016/j.eswa.2013.08.073

G. Mishne, Experiments with mood classification in blog posts, Proceedings of ACM SIGIR 2005 workshop on stylistic analysis of text for information access, vol.19, pp.321-327, 2005.

O. John, B. Donovan, and . Smyth, Trust in recommender systems, Proceedings of the 10th international conference on Intelligent user interfaces, pp.167-174, 2005.

U. Pavalanathan and J. Eisenstein, Emoticons vs. emojis on Twitter: A causal inference approach, 2015.

J. Michael, D. Pazzani, and . Billsus, Content-based recommendation systems, The adaptive web, pp.325-341, 2007.

P. T. Swiftkey, Most-used emoji revealed: Americans love skulls, Brazilians love cats, the French love hearts, vol.18, 2015.

T. N. Rubin, A. Chambers, P. Smyth, and M. Steyvers, Statistical topic models for multi-label document classification, Machine Learning, vol.88, pp.157-208, 2012.
DOI : 10.1007/s10994-011-5272-5

URL : https://link.springer.com/content/pdf/10.1007%2Fs10994-011-5272-5.pdf

C. Strobl, A. Boulesteix, T. Kneib, T. Augustin, and A. Zeileis, Conditional Variable Importance for Random Forests, BMC Bioinformatics, vol.9, p.307, 2008.
DOI : 10.1186/1471-2105-9-307

URL : https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/1471-2105-9-307?site=bmcbioinformatics.biomedcentral.com

, Emoji Research Team. 2015. Emoji Report, vol.40, 2015.

M. Thelwall, K. Buckley, G. Paltoglou, D. Cai, and A. Kappas, Sentiment strength detection in short informal text, Journal of the American Society for Information Science and Technology, vol.61, pp.2544-2558, 2010.

K. Trohidis, G. Tsoumakas, G. Kalliris, and I. P. Vlahavas, Multi-Label Classification of Music into Emotions, ISMIR, vol.8, pp.325-330, 2008.

G. Tsoumakas and I. Katakis, Multi-label classification: An overview, International Journal of Data Warehousing and Mining, vol.3, issue.3, 2006.

R. Xie, Z. Liu, R. Yan, and M. Sun, Neural Emoji Recommendation in Dialogue Systems, 2016.

M. Zhang and Z. Zhou, A Review on Multi-Label Learning Algorithms, IEEE Transactions on Knowledge and Data Engineering, vol.26, pp.1819-1837, 2014.