A Novel Dataset for Aspect-based Sentiment Analysis for Teacher Performance Evaluation

Published: 27 April 2023| Version 1 | DOI: 10.17632/b2yhc95rnx.1
Contributors:
Abhijit Bhowmik, Noorhuzaimi Mohd Noor, M Saef Ullah Miah, Mazid-Ul- Haque, Debajyoti Karmaker

Description

The dataset was created by collecting student feedback from American International University-Bangladesh and then labelled by undergraduate-level students into three sentiment classes: positive, negative, and neutral. The dataset was then cleaned and preprocessed to ensure data quality and consistency. The final dataset contains more than 2,000,000 student feedback instances related to teacher performance. This dataset can be used to develop and evaluate ABSA models for teacher performance evaluation.

Files

Institutions

  • American International University Bangladesh
  • Universiti Malaysia Pahang

Categories

Teacher Assessment, Sentiment Analysis

Licence