Sentiment analysis of student online interaction in a blended postgraduate programme
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Other Title
Authors
Pham, Truman
Vo, Darcy
Lindsay, L.
Pashna, Mohsen
Li, F.
Baker, Karen
Han, Binglan
Rowley, Rich
Vo, Darcy
Lindsay, L.
Pashna, Mohsen
Li, F.
Baker, Karen
Han, Binglan
Rowley, Rich
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Date
2019-02
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Conference Contribution - Oral Presentation
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
blended learning
Mind Lab (Unitec)
student engagement
narrative analysis
sentiment analysis (SA)
natural language generation (computer science)
Mind Lab (Unitec)
student engagement
narrative analysis
sentiment analysis (SA)
natural language generation (computer science)
ANZSRC Field of Research Code (2020)
Citation
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 the Scholarship of Technology Enhanced Learning (SoTEL) 2019, Auckland, New Zealand.
Abstract
RESEARCH QUESTIONS:
1. To what extent do students interact online?
2. What are the sentiments in student online interaction?
TML Blended Postgrad Programme
Online interaction on G+ Community
Sentiment analysis
Google Natural Language Processing
Research Methodology
Data Collection and Analysis
Overview of the collected data
Results - Number of Posts and Comments Each Category
Results - Monthly Posts and Comments
Results - Monthly Average of Score and Magnitude of Posts and Comments
Results - Box Plot for Sentiment Score in Each Category of G+ Community
Results - Box Plot for Sentiment Magnitude in Each Category of G+ Community
Discussion - What can we learn?
Conclusion
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