Title: Choosing technologies for education: a sentiment analysis and topic modelling approach on Twitter data

Authors: Junhe Yang; Scott J. Warren

Addresses: Department of Learning Technologies, College of Information, University of North Texas, 3940 N. Elm St., Suite G150, Denton, Texas, USA ' Department of Learning Technologies, College of Information, University of North Texas, 3940 N. Elm St., Suite G150, Denton, Texas, USA

Abstract: In today's educational landscape, the abundance of emerging educational technologies poses challenges for school leaders and teachers in making informed adoption decisions. Previous studies explored the sentiments and perspectives of teachers and students, but they had limited participation and didn't encompass diverse stakeholders. To address this gap, this study analysed 457,265 Twitter data to investigate widely retweeted content and frequently used hashtags in tweets regarding educational technology. The top ten retweeted tweets' creators represent the stakeholders had different roles, like non-profit organisation, educator, learning app company, and product manager. These retweets primarily focused on educational resources, technology tools, and job opportunities, with overall sentiments being mostly positive or neutral. While eMedicoz and damsdelhi, online medical education platforms, garnered positive sentiments, artificial intelligent and virtual reality evoked neutral responses. This study provides a robust framework for understanding the evolving landscape of educational technology, offering guidelines for responsible technology use in education.

Keywords: educational technology; sentiment analysis; topic modelling analysis; Twitter data.

DOI: 10.1504/IJSMILE.2025.150107

International Journal of Social Media and Interactive Learning Environments, 2025 Vol.7 No.2, pp.110 - 134

Received: 01 Feb 2024
Accepted: 06 Sep 2024
Published online: 01 Dec 2025 *

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