Altrabsheh, N., Cocea, M., & Fallahkhair, S. (2014a). Learning sentiment from student’s feedback for real-time interventions in classrooms. Lecture Notes in Computer Science, 8779, 40–49. Retrieved from http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6984506
Altrabsheh, N., Cocea, M., & Fallahkhair, S. (2014b). Sentiment Analysis: Towards a Tool for Analysing Real-Time Students Feedback. In International Conference on Tools with Artificial Intelligence, ICTAI (pp. 419–423). http://doi.org/10.1109/ICTAI.2014.70
Bing Liu. (2010). Sentiment Analysis and Subjectivity. In Handbook of Natural Language Processing (pp. 1–38). http://doi.org/10.1145/1772690.1772756
Feldman, R. (2013). Techniques and Applications for Sentiment Analysis. Communications of the ACM, 54(4), 82–89.
Guitart, I., Conesa, J., Villarejo, L., Lapedriza, A., Masip, D., Perez, A., & Planas, E. (2013). Opinion Mining on Educational Resources at the Open University of Catalonia. In 2013 Seventh International Conference on Complex, Intelligent, and Software Intensive Systems (pp. 385–390). IEEE. http://doi.org/10.1109/CISIS.2013.70
Haddi, E., Liu, X., & Shi, Y. (2013). The Role of Text Pre-processing in Sentiment Analysis. In Procedia Computer Science (Vol. 17, pp. 26–32). Elsevier B.V. http://doi.org/10.1016/j.procs.2013.05.005
Li, C., & Ma, J. (2012). Research on online education teacher evaluation model based on opinion mining. In National Conference on Information Technology and Computer Science (CITCS 2012) (pp. 1061–1064). http://doi.org/doi:10.2991/citcs.2012.264
Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies. (B. Liu, Ed.), Morgan & Claypool. Morgan & Claypool Publishers. http://doi.org/10.2200/S00416ED1V01Y201204HLT016
Manning, C. D., Raghavan, P., & Schutze, H. (2009). An Introduction to Information Retrieval. Cambridge University Press. http://doi.org/10.1109/LPT.2009.2020494
Mishra, N. ., & Jha, C. K. . (2014). An insight into task of opinion mining. In Lecture Notes of the Institute for Computer Sciences (Vol. 117, pp. 185–190). Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0- 84921384276&partnerID=40&md5=cb39ca050af23697b78393da851e2cc6
Murugananthan, V., & ShivaKumar, B. L. (2016). An adaptive educational data mining technique for mining educational data models in elearning systems. Indian Journal of Science and Technology, 9(3), 1–5. http://doi.org/10.17485/ijst/2016/v9i3/86392
Ortigosa, A., Martín, J. M., & Carro, R. M. (2014). Sentiment analysis in Facebook and its application to e-learning. Computers in Human Behavior, 31(1), 527–541. http://doi.org/10.1016/j.chb.2013.05.024
Pang, B., & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations & Trends in Information Retrieval, 2(1–2), 1–135.
Ravi, K., Ravi, V., Siddeshwar, V., & Mohan, L. (2015). Sentiment Analysis Applied to Educational Sector. In 2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). http://doi.org/10.1109/ICCIC.2015.7435667
Zarra, T., Chiheb, R., Faizi, R., & Afia, A. El. (2016). Using Textual Similarity and Sentiment Analysis in Discussions Forums to Enhance Learning. International Journal of Software Engineering and Its Applications, 10(1), 191–200.
Zhang, L., & Liu, B. (2014). Aspect and Entity Extraction for Opinion Mining. In Data Mining and Knowledge Discovery for Big Data (Vol. 1, pp. 1–40). http://doi.org/10.1007/978-3-642-40837-3