Paper Info
Title
Tracking The Public'S Opinion Of Online Education: A Quantitative Analysis Of Tweets On E-Learning
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.
Year
DOI
Venue
2019
10.1504/IJLT.2019.106550
INTERNATIONAL JOURNAL OF LEARNING TECHNOLOGY
Keywords
DocType
Volume
social media, latent Dirichlet allocation, LDA, online education, e-learning, electronic learning, tweets
Journal
14
Issue
ISSN
Citations 
4
1477-8386
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Andreas Giannakoulopoulos152.48
Alexandros Kouretsis200.34
Laida Limniati300.34