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Social media #MOOC mentions: lessons for MOOC research from analysis of Twitter data

Costello, Eamon ORCID: 0000-0002-2775-6006, Nair, Binesh, Brown, Mark ORCID: 0000-0002-7927-6717, Zhang, Jingjing ORCID: 0000-0002-0584-534X, Nic Giolla Mhichíl, Mairéad ORCID: 0000-0003-1885-6723, Donlon, Enda ORCID: 0000-0003-2817-9033 and Lynn, Theo ORCID: 0000-0001-9284-7580 (2016) Social media #MOOC mentions: lessons for MOOC research from analysis of Twitter data. In: ASCILITE 2016, 28-30 Nov 2016, Adelaide, Australia.

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Abstract

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.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:HCI; MOOCs; Data Analytics; Twitter; Social Media; Big Data
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > DCU Business School
DCU Faculties and Schools > NIDL (National Institute for Digital Learning)
DCU Faculties and Schools > Institute of Education > School of STEM Education, Innovation, & Global Studies
Published in: Ascilite Conference 2016, Proceedings. .
Official URL:http://2016conference.ascilite.org/wp-content/uploads/ascilite2016_costello_concise.pdf
Copyright Information:© 2017 The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:21716
Deposited On:07 Dec 2017 12:16 by Eamon Costello . Last Modified 16 Apr 2021 12:50

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