%0	Conference Proceedings
%A	Costello, Eamon
%A	Nair, Binesh
%A	Brown, Mark
%A	Zhang, Jingjing
%A	Giolla Mhichíl, Mairéad Nic
%A	Donlon, Enda
%A	Lynn, Theo
%C	Adelaide, Australia, Oceania
%D	2016
%E	Barker, Sandy
%E	Dawson, Shane
%E	Pardo, Abelardo
%E	Colvin, Cassandra
%K	Big Data
%K	data analytics
%K	HCI
%K	MOOCs
%K	social media
%K	Twitter
%P	157-162
%T	Social media #MOOC mentions: Lessons for MOOC research from analysis of Twitter data
%U	http://2016conference.ascilite.org/wp-content/uploads/ascilite2016_costello_concise.pdf
%X	There is a relative dearth of research into what is being said about MOOCs by users in social media, particularly through analysis of large datasets. In this paper we contribute to addressing this gap through an exploratory analysis of a Twitter dataset. We present an analysis of a dataset of tweets that contain the hashtag #MOOC. A three month sample of tweets from the global Twitter stream was obtained using the GNIP API. Using techniques for analysis of large microblogging datasets we conducted descriptive analysis and content analysis of the data. Our findings suggest that the set of tweets containing the hashtag #MOOC has some strong characteristics of an information network. Course providers and platforms are prominent in the data but teachers and learners are also evident. We draw lessons for further research based on our findings.
%8	11/2016
%*	yes
%>	http://www.oerknowledgecloud.org/archive/ascilite2016_costello_concise.pdf