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

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

Shalin Hai-Jew
Copyright: © 2023 |Pages: 40
ISBN13: 9781668471234|ISBN10: 166847123X|EISBN13: 9781668471241
DOI: 10.4018/978-1-6684-7123-4.ch066
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MLA

Hai-Jew, Shalin. "Peripheral Vision: Engaging Multimodal Social Media Datasets to Differentiate MOOC Platforms by Course Offerings and Us." Research Anthology on Applying Social Networking Strategies to Classrooms and Libraries, edited by Information Resources Management Association, IGI Global, 2023, pp. 1219-1258. https://doi.org/10.4018/978-1-6684-7123-4.ch066

APA

Hai-Jew, S. (2023). Peripheral Vision: Engaging Multimodal Social Media Datasets to Differentiate MOOC Platforms by Course Offerings and Us. In I. Management Association (Ed.), Research Anthology on Applying Social Networking Strategies to Classrooms and Libraries (pp. 1219-1258). IGI Global. https://doi.org/10.4018/978-1-6684-7123-4.ch066

Chicago

Hai-Jew, Shalin. "Peripheral Vision: Engaging Multimodal Social Media Datasets to Differentiate MOOC Platforms by Course Offerings and Us." In Research Anthology on Applying Social Networking Strategies to Classrooms and Libraries, edited by Information Resources Management Association, 1219-1258. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-6684-7123-4.ch066

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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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