Title: Tracking the public's opinion of online education: a quantitative analysis of tweets on e-learning
Authors: Andreas Giannakoulopoulos; Alexandros Kouretsis; Laida Limniati
Addresses: Department of Audio and Visual Arts, Ionian University, 7, Tsirigoti square, 49100, Corfu, Greece ' Interactive Arts Laboratory, Ionian University, 7, Tsirigoti square, 49100, Corfu, Greece ' Interactive Arts Laboratory, Ionian University, 7, Tsirigoti square, 49100, Corfu, Greece
Abstract: The aim of this paper is to analyse what kind of information related to e-learning is circulating in social media and in particular in Twitter from the perspective of someone who searches on Twitter. This paper is an attempt to discover in what extend is Twitter being used as a tool for e-learning and consequently collaboration. This paper analyses approximately 156,000 tweets regarding online education in order to evaluate the type of information circulating in this kind of discourse. In this way, it could be used from educators who are thinking of including Twitter as a tool for an online course. The tweets were gathered in spring 2018 using R programming language. For analysing and visualising the patterns encoded in tweets, we rely on the effectiveness of topic modelling using LDA. The dataset is composed by tweets extracted from Twitter API on e-learning related queries. The results indicate the prevalence of one-way promotional material over bidirectional discussions among users. This implies a necessity for quality control of educational information on social media and a need to motivate the educational community to participate to a larger extent in related discussions.
Keywords: social media; latent Dirichlet allocation; LDA; online education; e-learning; electronic learning; tweets.
International Journal of Learning Technology, 2019 Vol.14 No.4, pp.271 - 287
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 30 Mar 2020 *