Social Media MOOC Mentions - iHCI 2016
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Amidst the hype and the hysteria MOOCs themselves have marched steadily along. Recent reports show that they continue to grow both in numbers of courses being offered and the total number of learners enrolled on all MOOCs. And so, despite many critiques and uncertainties about their true role and financial viability, MOOCs are for the moment at least, here to stay. The cMOOC xMOOC binary, and other acronymic derivations, can be seen as representative of the contestation of the arena in which MOOCs are situated; as attempts to frame or direct the discourse. This has been examined in the academic literature REFS, in the traditional media [VITOMIR SELWIN US ] and to some degree in social media [REFS]. In this paper will examine how stakeholders including MOOC providers, teachers and students use the term MOOC in social medium Twitter. We do this through an analysis of a sample of mentions of the hashtag “#MOOC”. Furthermore, we examine issues of the how research can be conducted on MOOCs in Twitter including an appraisal of how the term itself is both portrayed and conceptualized in this space.
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Social Media MOOC Mentions - iHCI 2016
- 1. Social Media #MOOC Mentions: Lessons for MOOC Research from Analysis of Twitter Data Eamon Costello 1, Mark Brown1, Binesh Nair1 Jingjing Zhang 2 Enda Donlon 1, Mairéad Nic Giolla Mhichíl 1, Theo Lynn1 1. Dublin City University 2. Beijing Normal University
- 4. Horrigan, J. (2016). Lifelong learning and technology. Pew Research Center. Available from http://www.pewinternet.org/2016/03/22/lifelong-learning-and- technology/ n = 2,752
- 5. • 50,274 n = 50,274 Dahlstrom, E., Christopher Brooks, D., Grajek, S., and Reeves, R. (2015) ECAR Study of Students and Information Technology, 2015. Research report. Louisville, CO: ECAR, December 2015. Available from https://library.educause.edu/resources/2015/8/2015-student-and-faculty-technology-research-studies
- 8. Background BigEdData project research collaboration What can learn about #MOOCs from Twitter?
- 9. Researching MOOCs What is being said about MOOCs on Twitter?
- 10. What do we know
- 11. What do we know?
- 12. Whatdo we know?
- 13. Whatdo we know?
- 14. Whatwe don’t know How can we identify different user types in MOOC Twitter networks? What are communication characteristics of MOOC Twitter users?
- 15. Data and Methods by RSNY • GNIP API Sep – Dec 2015 -> find #MOOC • GZIP -> JSON- > MongoDB – > R • 32,309 tweets (17,910 original) • Descriptive analytics, content analytics, network analytics (Chae, 2015; Lynn et. al., 2015) Chae, B. K. 2015. Insights from hashtag# supplychain and Twitter Analytics: Considering Twitter and Twitter data for supply chain practice and research. In International Journal of Production Economics, 165, 247-259. Lynn, T., Kilroy, S., van der Werff, L., Healy, P., Hunt, G., Venkatagiri, S., and Morrison, J. 2015. Towards a general research framework for social media research using big data. In Professional Communication Conference (IPCC), 2015 IEEE International (pp. 1-8). IEEE.
- 16. Top 25 Words in the MOOC Dataset Word Frequency Word Frequency Word Frequency mooc 21,199 education 1,126 onlinelearn 501 course 2,733 join 1,113 science 492 learn 2,686 start 1,055 marketing 478 online 2,442 register 954 Data 471 elearn 2,079 onlinecourse 736 Life 447 free 1,911 highered 667 coursera 1,410 digital 562 Edxonline 1,332 university 556 edtech 1,259 open 520 business 1,165 students 518
- 17. Top Hashtags
- 18. Peak Tweets Num Topic 33 Promotion of MOOC on “Cognitive Technology and its growing importance for business” by David Schatsky, course instructor and senior manager Deloitte LLP. 72 Promotion of Deloitte’s MOOC on 3D printing. 31 Successful Societies (by Princeton University) promoting MOOC on ‘How can Governments Improve Citizen Services and Cabinet Office Coordination.’ 54 Successful Societies promoting MOOC on ‘Making Government work in Hard Places’. 40 Successful Societies promoting MOOC on ‘How Leaders Overcome Governance Challenges’. 53 Successful Societies promoting MOOC on ‘Writing Science of Delivery Case Studies’ 58 NutritionMOOCs promoting MOOC on ‘Nutrition and Health: Micronutrients and Malnutrition’. 182 NutritionMOOCs promoting 2nd part of MOOC on Nutrition and Health from Wageningen University. 30 Promotion of Coursera’s MOOC on ‘Training TESOL Certificate Part 1: Teach English’. 43 Retweet of Quizalizeapp’s tweet ‘How to say Merry Christmas in 77 Languages’.
- 20. Sentiment Analysis Avg: 0.095 Exemplar Tweet Sentiment Score @thesiswhisperer I think the #MOOC is providing wonderful supportive pillow of trust & honesty- glad I'm taking part- thank u #survivephd15 6 STUNNING #mathed animations from .@robertghrist in his calculus #MOOC. Beautiful and effective. Kudos. http://t.co/GgdN2KHFZf 4 Just discovered a great free #Social Innovation online course, on this cool learning platform - #iVersity #MOOC ~ http://t.co/kGPzmqONFq 4 #ememitalia Teixeira: focusing on dropout as a problem to criticize #MOOC education is a conceptual mistake -4 CloudComputingApplications - definitely the worst @coursera #MOOC I've ever taken. Irrelevant videos & useless tuts #unenrolled -3 Exemplar Tweets with Strong Sentiment
- 21. Conceptualizing Networks Communication types (Brunns & Stieglitz, 2014) • Annunciative • Conversational • Disseminative Bruns, Axel & Stieglitz, Stefan (2014) Metrics for Understanding Communication on Twitter. In Weller, Katrin, Bruns, Axel, Burgess, Jean, Mahrt, Merja, & Puschmann, Cornelius (Eds.) Twitter and Society. Peter Lang, New York, pp. 69-82.
- 22. Conceptualizing the network Information network or social network? (Myers, Sharma, Gupta & Lin, 2014) Myers, S. A., Sharma, A., Gupta, P., & Lin, J. (2014). 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). ACM.
- 23. Key Hubs (based on follows) Screen Name BC Screen Name BC Screen Name BC mooc24 66,620 openSAP 842 CourseBuffet 118 NutritionMOOC s 52,116 UCTMOOCs 689 PythonDaily 106 EUmoocs 24,171 openHPI 499 OpenClassrooms 74 tleerwerk 14,182 MIT 443 EducationDive 64 juandoming 4,141 Plusacumen 435 Acumen 50 Mirimi 3,043 Hubert_edu 390 iversity 2,715 CircularX 330 FutureLearn 1,844 ColumbiaScience 325 nancyrubin 1,614 KristerSvensson 192 MOOCFactory 900 Drchuck 167.50
- 24. Key Hubs (based on @replies) Screen Name BC Screen Name BC Screen Name BC CraigTaylor74 261 Diando70 16 Judyfranks 3 LearnKotch 209 Yishaym 15 juandoming 3 NUsocialmktg 173 AleksejHeinze 12 AdrianaGWilde 3 Kiwirip [Peter Mellow] 168 TESSIndia 10 catspyjamasnz 3 RandyHlavac 138 DarcoJansen 9 culturalprovoca 3 LHTL_MOOC 109 Esrimooc 6 zaidlearn 80 ECOmooc 6 MdCplus 55 EUmoocs 4 MGCleve 48 KR_Barker 4 edXOnline 34 mbrownz 4
- 25. Future work • What can we learn from MOOC hashtags?
- 26. Questions? Go raibh maith agaibh eamon.costello@dcu.ie @eam0
Editor's Notes
- MMORPG - Massively multiplayer online role-playing games The term MOOC is credited to Dave Cormier of the University of Prince Edward Island. He coined the term to describe a course called Connectivism and Connective Knowledge (CCK08). CCK08, which was led by George Siemens of Athabasca University and Stephen Downes of the National Research Council. The course had 25 fee paying students as well as 2200 online learners who participated for free.
- MMORPG - Massively multiplayer online role-playing games The term MOOC is credited to Dave Cormier of the University of Prince Edward Island. He coined the term to describe a course called Connectivism and Connective Knowledge (CCK08). CCK08, which was led by George Siemens of Athabasca University and Stephen Downes of the National Research Council. The course had 25 fee paying students as well as 2200 online learners who participated for free. cMOOC xMOOC SPOCS, DOCCs BOOCs LOOCs MOORs SMOCs
- Big Data Center for Technology-Mediated Education
- Big Data Center for Technology-Mediated Education
- Big Data Center for Technology-Mediated Education
- very little research has been undertaken into how MOOCs are portrayed in social media platforms such as Twitter. Studies to date have largely been of small datasets taking a sample of manually extracted tweets from a time period One study of note in this area looked at users of the Sina Weibo platform, a popular Chinese microblogging website [8]. This study screen-scraped 95,015 postings with mentions of MOOC published by 62,074 users on Sina Weibo for a for year period and analyzed the volume of postings according to four time frames: by year, by month, by day of the week, and by the time of day. Their work outlined some trends and made an exploratory foray into this topic.
- very little research has been undertaken into how MOOCs are portrayed in social media platforms such as Twitter. Studies to date have largely been of small datasets taking a sample of manually extracted tweets from a time period
- Study from 2013 of just over 4,000 tweets (~1209 oon OER and 18,000 on Twitter) suggested that the public are now forming informed opinions regarding OER whereas caution and skepticism still surrounds the relatively new concept of MOOC.
- very little research has been undertaken into how MOOCs are portrayed in social media platforms such as Twitter. Studies to date have largely been of small datasets taking a sample of manually extracted tweets from a time period One study of note in this area looked at users of the Sina Weibo platform, a popular Chinese microblogging website [8]. This study screen-scraped 95,015 postings with mentions of MOOC published by 62,074 users on Sina Weibo for a for year period and analyzed the volume of postings according to four time frames: by year, by month, by day of the week, and by the time of day. Their work outlined some trends and made an exploratory foray into this topic.
- One study of note in this area looked at users of the Sina Weibo platform, a popular Chinese microblogging website [8]. This study screen-scraped 95,015 postings with mentions of MOOC published by 62,074 users on Sina Weibo for a for year period and analyzed the volume of postings according to four time frames: by year, by month, by day of the week, and by the time of day. Their work outlined some trends and made an exploratory foray into this topic.
- One study of note in this area looked at users of the Sina Weibo platform, a popular Chinese microblogging website [8]. This study screen-scraped 95,015 postings with mentions of MOOC published by 62,074 users on Sina Weibo for a for year period and analyzed the volume of postings according to four time frames: by year, by month, by day of the week, and by the time of day. Their work outlined some trends and made an exploratory foray into this topic.
- Twitter data for the MOOC dataset was extracted from GNIP API for the period of September – December 2015 and augmented with additional data including Klout Score (a Social Network Influencer Score), geographic location and URL expansion. ‘#MOOC’ was used to as a keyword to extract the required data. 32,00
- Sentiment analysis is used to examine overall orientation (positive and negative) and intensity (strong or weak) of opinions in text (Pang & Lee, 2008). Sentiment analysis is widely used in Twitter content analysis and has been found to reflect the landscape of the offline world (Bae & Lee, 2012; Siapera et al, 2015; Chae, 2015; Lynn et al. 2015). ‘qdap’ library in R was used to perform sentiment analysis on this dataset. There were 17,910 sentences and 345,067 words. The average sentiment was found to be 0.095; suggesting that the tweets are highly neutral.
- Qdap library Hu and Liu’s opinion lexicon was loaded into R workspace (Hu et al., 2005). This lexicon has categorized nearly 6,800 words as positive or negative. The lexicon consists of two text files, one containing a list of positive words and the other containing a list of negative words. The sentiment of a tweet is calculated based on the number of words it has from either of the lists.
- draw distinctions between users who take a largely annunciative approach (mainly original tweets), conversational approach (mainly @replies), or disseminative approach (mainly retweets). Bruns, Axel & Stieglitz, Stefan (2014) Metrics for Understanding Communication on Twitter. In Weller, Katrin, Bruns, Axel, Burgess, Jean, Mahrt, Merja, & Puschmann, Cornelius (Eds.) Twitter and Society. Peter Lang, New York, pp. 69-82.
- The million follow fallacy
- Hubs (sometimes termed as brokers) represent the backbone of any network since they facilitate the connections between users. In other words, these users act as hubs for other users to engage in the network. There are key hubs in the #MOOC dataset as is evident from small values for key network statistics like, average path length and network diameter. Key hubs in the network were identified using the network statistic betweenness centrality (BC). Key hubs tend to have a higher score for the betweenness centrality. Betweenness Centrality measures how often a node fall in between the path of communication between any two nodes in the network. Key hubs tend to have a higher score for betweeness centrality. OpenHPI - educational Internet platform of the German Hasso Plattner Institute, Potsdam OpenSAP The Hasso Plattner Institute was founded in 1998 and is the first, and still the only entirely privately funded university college in Germany. It is financed entirely through private funds donated by its founder, Prof. Dr. h.c. Hasso Plattner, who co-founded the largest European software company SAP SE, and is currently the chairman of SAP's supervisory board.
- Peter Mellow @kiwirip James Little @jimjamyahauk