Encyclopedia of Educational Innovation

Living Edition
| Editors: Michael A. Peters, Richard Heraud

Sentiment Analysis in Education

  • Darcy VoEmail author
  • Truman Pham
Living reference work entry
DOI: https://doi.org/10.1007/978-981-13-2262-4_138-1

Defining Sentiment Analysis

The term sentiment analysis, in the research field and this entry, refers to a process used to determine the sentiments (general feelings, attitudes, or opinions) of the writers expressed through text. The process includes gathering data, preprocessing textual data to extract opinionated data, and then classifying the data into positive, neutral, or negative sentiments (Liu 2012; Thelwall 2016). For example, when a student writes feedback saying, “it’s an interesting lecture,” the program will pick up the opinionated word “interesting” and assign a positive sentiment score to the text. All the steps in the process of sentiment analysis are done automatically using computer programs. Sentiment analysis pays attention to the overall feelings or attitudes present in the text rather than the content of the topic that the text is written about.


The idea of learning about people’s opinions or attitudes towards a product, a service, or a public figure...

This is a preview of subscription content, log in to check access.


  1. Altrabsheh, N., Cocea, M., & Fallahkhair, S. (2014). Sentiment analysis: towards a tool for analysing real-time students’ feedback. In: Proceedings of the IEEE International Conference on Tools with Artificial Intelligence, ICTAI, pp. 419–423.  https://doi.org/10.1109/ICTAI.2014.70.
  2. Colace, F., De Santo, M., & Greco, L. (2014). SAFE: A sentiment analysis framework for e-learning. International Journal of Emerging Technologies in Learning (IJET), 9(6), 37.  https://doi.org/10.3991/ijet.v9i6.4110.CrossRefGoogle Scholar
  3. Liu, B. (2012). Sentiment analysis and opinion mining. San Rafael: Morgan & Claypool.CrossRefGoogle Scholar
  4. Mäntylä, M., Graziotin, D., & Kuutila, M. (2018). The evolution of sentiment analysis – A review of research topics, venues, and top cited papers. Computer Science Review, 27, 16–32.  https://doi.org/10.1016/j.cosrev.2017.10.002.CrossRefGoogle Scholar
  5. Ozturk, Z. K., Cicek, Z. E., & Ergul, Z. (2017). Sentiment analysis: An application to Anadolu University. Acta Physica Polonica A, 132(3), 753–755.CrossRefGoogle Scholar
  6. Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends® in Information Retrieval, 2(1–2), 1–135.  https://doi.org/10.1561/1500000011.CrossRefGoogle Scholar
  7. Pham, T., Vo, D., Lindsay, L., Li, F., Pashna, M., Baker, K., Han, B., & Rowley, R. (2019, February). Sentiment analysis of student online interaction in a blended postgraduate programme. Paper presented at SoTEL symposium. Auckland, 14 Feb 2019.Google Scholar
  8. Rani, S., & Kumar, P. (2017). Sentiment analysis system to improve teaching and learning. Computer, 50(5), 36–43.  https://doi.org/10.1109/MC.2017.133.CrossRefGoogle Scholar
  9. Thelwall, M. (2016). Sentiment analysis. In L. Sloan & A. Quan-Haase (Eds.), The SAGE handbook of social media research methods (pp. 545–556). London: Sage.  https://doi.org/10.4135/9781473983847.CrossRefGoogle Scholar
  10. Varsha, K., & Monica, R. (2018). Analyzing of premier institution using twitter data on real-time basis. In: 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017, pp. 2811–2814.  https://doi.org/10.1109/ICECDS.2017.8389968.
  11. Vohra, S., & Teraiya, J. (2013). A comparative study of sentiment analysis techniques. Journal of Information, Knowledge and Research in Computer Engineering, 2(2), 313–317.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.The Mind LabAucklandNew Zealand

Section editors and affiliations

  • David Parsons
    • 1
  1. 1.The Mind LabAucklandNew Zealand