1. Agarwal, A., Xie, B., Vovsha, I., Rambow, O., Passonneau, R., 2011. Sentiment analysis of twitter data, in: Proceedings of the workshop on languages in social media, Association for Computational Linguistics. pp. 30–38.
2. Azzouza, N., Akli-Astouati, K., Oussalah, A., Bachir, S.A., 2017. A real-time twitter sentiment analysis using an unsupervised method, in: Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics, ACM, New York, NY, USA. pp. 15:1–15:10. URL: http://doi.acm.org/10.1145/3102254.3102282, doi:10.1145/3102254.3102282.
3. Bakliwal, A., Arora, P., Madhappan, S., Kapre, N., Singh, M., Varma, V., 2012. Mining sentiments from tweets., in: WASSA@ ACL, pp. 11–18.
4. Clark, S., Wicentwoski, R., 2013. Swatcs: Combining simple classifiers with estimated accuracy., in: SemEval@ NAACL-HLT, pp. 425–429.
5. Coletta, L.F.S., da Silva, N.F.F., Hruschka, E.R., Hruschka, E.R., 2014. Combining classification and clustering for tweet sentiment analysis,in: Intelligent Systems (BRACIS), 2014 Brazilian Conference on, IEEE. pp. 210–215.