H. Binali, C. Wu, and V. Potdar, Computational approaches for emotion detection in text, 4th IEEE International Conference on Digital Ecosystems and Technologies, pp.172-177, 2010.
DOI : 10.1109/DEST.2010.5610650
URL : https://espace.curtin.edu.au/bitstream/20.500.11937/36906/2/152155_152155.pdf

A. D. Kramer, J. E. Guillory, and J. T. Hancock, Experimental evidence of massivescale emotional contagion through social networks, Proc. Natl. Acad. Sci, pp.8788-8790, 2014.
DOI : 10.1073/pnas.1320040111
URL : http://www.pnas.org/content/111/24/8788.full.pdf

T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean, Distributed representations of words and phrases and their compositionality, Advances in NIPS, pp.3111-3119, 2013.

B. Pang and L. Lee, Opinion Mining and Sentiment Analysis, Foundations and Trends?? in Information Retrieval, vol.2, issue.1???2, pp.1-135, 2008.
DOI : 10.1561/1500000011

W. Qiyao, L. Zhengmin, J. Yuehui, C. Shiduan, and Y. Tan, ULM: A user-level model for emotion prediction in social networks, The Journal of China Universities of Posts and Telecommunications, vol.23, issue.3, pp.63-88, 2016.
DOI : 10.1016/S1005-8885(16)60034-1

Y. Rao, J. Lei, L. Wenyin, Q. Li, and M. Chen, Building emotional dictionary for sentiment analysis of online news, World Wide Web, vol.17, issue.1, pp.723-742, 2014.
DOI : 10.3115/1621474.1621487

F. N. Ribeiro, M. Araújo, P. Gonçalves, M. A. Gonçalves, and F. Benevenuto, SentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methods, EPJ Data Science, vol.112, issue.8, pp.1-29, 2016.
DOI : 10.1073/pnas.1411678112

J. Staiano and M. Guerini, DepecheMood: a lexicon for emotion analysis from crowdannotated news, Proceedings of the 52nd Annual Meeting of the ACL, pp.427-433, 2014.
DOI : 10.3115/v1/p14-2070
URL : https://doi.org/10.3115/v1/p14-2070