Analyzing Tweets Using Topic Modeling and ChatGPT: What We Can Learn About Teachers and Topics During COVID-19 Pandemic-Related School Closures

Anna Weigand, Anna Weigand, Maj Jacob, Maria Rauschenberger, Maria José Escalona Cuaresma

2024

Abstract

This study examines the shifting discussions of teachers within the #twlz community on Twitter across three phases of the COVID-19 pandemic – before school closures and during the first and second school closures. We analyzed tweets from January 2020 to May 2021 to identify topics related to education, digital transformation, and the challenges of remote teaching. Using machine learning and ChatGPT, we categorized discussions that transitioned from general educational content to focused dialogues on online education tools during school closures. Before the pandemic, discussions were generally focused on education and digital transformation. During the first school closures, conversations shifted to more specific topics, such as online education and tools to adapt to distance learning. Discussions during the second school closures reflected more precise needs related to fluctuating pandemic conditions and schooling requirements. Our findings reveal a consistent increase in the specificity and urgency of the topics over time, particularly regarding digital education.

Paper Citation

in Harvard Style

Weigand A., Jacob M., Rauschenberger M. and Escalona Cuaresma M. (2024). Analyzing Tweets Using Topic Modeling and ChatGPT: What We Can Learn About Teachers and Topics During COVID-19 Pandemic-Related School Closures. In Proceedings of the 20th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST; ISBN 978-989-758-718-4, SciTePress, pages 350-357. DOI: 10.5220/0013036900003825

in Bibtex Style

@conference{webist24,
author={Anna Weigand and Maj Jacob and Maria Rauschenberger and Maria José Escalona Cuaresma},
title={Analyzing Tweets Using Topic Modeling and ChatGPT: What We Can Learn About Teachers and Topics During COVID-19 Pandemic-Related School Closures},
booktitle={Proceedings of the 20th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST},
year={2024},
pages={350-357},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013036900003825},
isbn={978-989-758-718-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST
TI - Analyzing Tweets Using Topic Modeling and ChatGPT: What We Can Learn About Teachers and Topics During COVID-19 Pandemic-Related School Closures
SN - 978-989-758-718-4
AU - Weigand A.
AU - Jacob M.
AU - Rauschenberger M.
AU - Escalona Cuaresma M.
PY - 2024
SP - 350
EP - 357
DO - 10.5220/0013036900003825
PB - SciTePress