#MOOC Friends and Followers: An Analysis of Twitter Hashtag Networks

  • Eamon CostelloEmail author
  • Mark Brown
  • Binesh Nair
  • Mairéad Nic Giolla Mhichíl
  • Jingjing Zhang
  • Theo Lynn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10254)


In this paper we present results of the initial phase of a project which sought to analyze the community who use the hashtag #MOOC in Twitter. We conceptualize this community as a form of networked public. In doing so we ask what the nature of this public is and whether it may be best conceived of as a social or informational network. In addition we seek to uncover who the stakeholders are who most influentially participate. We do this by using Social Network Analysis (SNA) to uncover the key hubs and influencers in the network. We use two approaches to deriving a network typology - one based on follows and on based on replies and compare and contrast the results.


MOOCs Twitter Social network analysis Networked publics 


  1. 1.
    Bulfin, S., Pangrazio, L., Selwyn, N.: Making “MOOCs”: the construction of a new digital higher education within news media discourse. Int. Rev. Res. Open Distance Learn. 15, 290–305 (2014)Google Scholar
  2. 2.
    Kovanovic, V., Joksimovic, S., Gavsevic, D., et al.: What public media reveals about MOOCs: a systematic analysis of news reports. Br. J. Edu. Technol. 46, 510–527 (2015)CrossRefGoogle Scholar
  3. 3.
    Brown, M., Costello, E., Donlon, E., Giolla-Mhichil, M.: MOOCs in the news: the ‘real’ story behind the irish story. In: Global Learn, vol. 2016, no. 1, pp. 337–345 (2016)Google Scholar
  4. 4.
    Abeywardena, I.S.: Public opinion on OER and MOCC: a sentiment analysis of Twitter data (2014)Google Scholar
  5. 5.
    Shen, C., Kuo, C.-J.: Learning in massive open online courses: evidence from social media mining. Comput. Hum. Behav. 51, 568–577 (2015)CrossRefGoogle Scholar
  6. 6.
    Zhang, J., Perris, K., Zheng, Q., Chen, L.: Public response to “the MOOC movement” in China: examining the time series of microblogging. Int. Rev. Res. Open Distrib. Learn. 16, 144–160 (2015)CrossRefGoogle Scholar
  7. 7.
    Myers, S.A., Sharma, A., Gupta, P., Lin, J.: Information network or social network?: the structure of the twitter follow graph. In: Proceedings of the 23rd International Conference on World Wide Web, pp. 493–498 (2014)Google Scholar
  8. 8.
    Chae, B.K.: Insights from hashtag# supplychain and Twitter analytics: considering Twitter and Twitter data for supply chain practice and research. Int. J. Prod. Econ. 165, 247–259 (2015)CrossRefGoogle Scholar
  9. 9.
    Lynn, T., Healy, P., Kilroy, S., Hunt, G., van der Werff, L., Venkatagiri, S., Morrison, J.: Towards a general research framework for social media research using big data. In: Proceedings of 2015 IEEE International Professional Communication Conference (IPCC), pp. 1–8. IEEE (2015)Google Scholar
  10. 10.
    Costello, E., Binesh, N., Brown, M., Zhang, J., Nic Giolla-Mhichíl, M., Donlon, E., Lynn, T.: Social media #MOOC mentions: lessons for MOOC mentions from analysis of Twitter data. In: Barker, S., Dawson, S., Pardo, A., Colvin, C (eds.) Proceedings ASCILITE 2016 Adelaide, pp. 157–162 (2016)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Eamon Costello
    • 1
    Email author
  • Mark Brown
    • 1
  • Binesh Nair
    • 1
  • Mairéad Nic Giolla Mhichíl
    • 1
  • Jingjing Zhang
    • 2
  • Theo Lynn
    • 1
  1. 1.Dublin City UniversityDublinIreland
  2. 2.Beijing Normal UniversityBeijingChina

Personalised recommendations