Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. J. Mach. Learn. Res., 3, 993–1022. Retrieved from

Hutto, C. J., & Gilbert, E. (2014). VADER: A parsimonious rule-based model for sentiment analysis of social media text. In E. Adar, P. Resnick, M. D. Choudhury, B. Hogan, & A. H. Oh (Eds.), ICWSM. The AAAI Press. Retrieved from

Jagarlamudi, J., Daumé, H., III, & Udupa, R. (2012). Incorporating lexical priors into topic models. In Proceedings of the 13th conference of the european chapter of the association for computational linguistics (pp. 204–213). Stroudsburg, PA, USA: Association for Computational Linguistics. Retrieved from

Li, F., Huang, M., & Zhu, X. (2010). Sentiment analysis with global topics and local dependency. In Proceedings of the twenty-fourth aaai conference on artificial intelligence (pp. 1371–1376). Atlanta, Georgia: AAAI Press. Retrieved from

Medhat, W., Hassan, A., & Korashy, H. (2014). Sentiment analysis algorithms and applications: A survey. In.

Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. CoRR, abs/1301.3781. Retrieved from

Pennington, J., Socher, R., & Manning, C. D. (2014). GloVe: Global vectors for word representation. In Empirical methods in natural language processing (emnlp) (pp. 1532–1543). Retrieved from