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Topic based quality indexes assessment through sentiment.

Marco Ortu1, Luca Frigau1, Giulia Contu1

  • 1Department of Economics and Business Sciences, University of Cagliari, Viale Fra Ignazio 17, Cagliari, 09123 Italy.

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|September 26, 2022
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Summary
This summary is machine-generated.

This study introduces TOpic modeling Based Index Assessment through Sentiment (TOBIAS), a new method to analyze how comment topics and sentiments influence overall ratings. TOBIAS offers interpretable insights into student feedback on university courses.

Keywords:
Complex analysisMultivariate analysisPartial least squaresStudent satisfactionUniversity

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Area of Science:

  • Social Sciences
  • Data Science
  • Educational Assessment

Background:

  • Understanding student feedback is crucial for improving educational quality.
  • Existing methods may not fully capture the nuanced relationship between comment content, sentiment, and overall evaluations.
  • A comprehensive approach is needed to link specific topics and sentiments to performance ratings.

Purpose of the Study:

  • To propose and validate a novel methodology, TOpic modeling Based Index Assessment through Sentiment (TOBIAS).
  • To model the impact of comment topics, moods, and sentiments on the overall rating of a phenomenon.
  • To provide interpretable results on how student feedback influences course quality assessments.

Main Methods:

  • Combining Sentiment Analysis to identify emotions and moods.
  • Utilizing Topic Modeling to extract key themes from comments.
  • Employing Partial Least Square Path Modeling to quantify the influence of topics and sentiments on overall ratings.

Main Results:

  • The TOBIAS methodology successfully modeled the relationship between comment content, sentiment, and overall ratings.
  • Interpretable results were generated, demonstrating the impact of specific topics and sentiments on student evaluations.
  • The case study on university course quality provided empirical validation for the TOBIAS approach.

Conclusions:

  • TOBIAS offers a robust framework for analyzing qualitative feedback to understand quantitative outcomes.
  • The method effectively links expressed sentiments and discussed topics to overall performance ratings.
  • This approach can be valuable for quality assessment in various domains, including education.