Sentiment analysis: towards a tool for analysing real-time students feedback

Nabeela Altrabsheh, Mihaela Cocea, Sanaz Fallahkhair

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBN

Abstract

Students' real-time feedback has numerous advantages in education, however, analysing feedback while teaching is both stressful and time consuming. To address this problem, we propose to analyse feedback automatically using sentiment analysis. Sentiment analysis is domain dependent and although it has been applied to the educational domain before, it has not been previously used for real-time feedback. To find the best model for automatic analysis we look at four aspects: preprocessing, features, machine learning techniques and the use of the neutral class. We found that the highest result for the four aspects is Support Vector Machines (SVM) with the highest level of preprocessing, unigrams and no neutral class, which gave a 95 percent accuracy.
Original languageEnglish
Title of host publicationIEEE 26th international conference on tools with artificial intelligence
Place of PublicationLimassol, Cyprus
PublisherIEEE
Pages419-423
Number of pages5
DOIs
Publication statusPublished - 31 Dec 2014
EventIEEE 26th international conference on tools with artificial intelligence - Limassol, Cyprus, 10-12 Nov. 2014
Duration: 31 Dec 2014 → …

Conference

ConferenceIEEE 26th international conference on tools with artificial intelligence
Period31/12/14 → …

Bibliographical note

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Keywords

  • Sentiment Analysis
  • Educational Data Mining
  • Feature Selection
  • Real-time Feedback

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  • Cite this

    Altrabsheh, N., Cocea, M., & Fallahkhair, S. (2014). Sentiment analysis: towards a tool for analysing real-time students feedback. In IEEE 26th international conference on tools with artificial intelligence (pp. 419-423). IEEE. https://doi.org/10.1109/ICTAI.2014.70