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Peripheral Vision: Engaging Multimodal Social Media Datasets to Differentiate MOOC Platforms by Course Offerings and User Bases

Peripheral Vision: Engaging Multimodal Social Media Datasets to Differentiate MOOC Platforms by Course Offerings and User Bases

Copyright: © 2019 |Pages: 43
ISBN13: 9781522575283|ISBN10: 1522575286|ISBN13 Softcover: 9781522587491|EISBN13: 9781522575290
DOI: 10.4018/978-1-5225-7528-3.ch008
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MLA

Shalin Hai-Jew. "Peripheral Vision: Engaging Multimodal Social Media Datasets to Differentiate MOOC Platforms by Course Offerings and User Bases." Methods for Analyzing and Leveraging Online Learning Data, IGI Global, 2019, pp.168-210. https://doi.org/10.4018/978-1-5225-7528-3.ch008

APA

S. Hai-Jew (2019). Peripheral Vision: Engaging Multimodal Social Media Datasets to Differentiate MOOC Platforms by Course Offerings and User Bases. IGI Global. https://doi.org/10.4018/978-1-5225-7528-3.ch008

Chicago

Shalin Hai-Jew. "Peripheral Vision: Engaging Multimodal Social Media Datasets to Differentiate MOOC Platforms by Course Offerings and User Bases." In Methods for Analyzing and Leveraging Online Learning Data. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-7528-3.ch008

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Abstract

In the dozen years since massive open online courses (MOOCs) have been a part of open-source online learning, the related platforms and technologies have settled out to some degree. This chapter indirectly explores 10 of the most well-known MOOC platforms based on social data from the following sources: large-scale web search data (via Google Correlate), academic research indexing (Google Scholar), social imagery and related image tagging (Google Image Search), crowd-sourced articles from a crowd-sourced encyclopedia (Wikipedia), microblogging data (Twitter), and posts and comments from social networking data (Facebook). This analysis is multimodal, to include text and imagery, and the analyses are enabled by various forms of “distant reading,” including topic modeling, sentiment analysis, and computational text analysis, and manual coding of social imagery. This chapter aims to define MOOC platforms indirectly by their course contents and the user bases (and their social media-based discourses) that have grown up around each.

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