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Clickbait in Education—Positive or Negative? Machine Learning Answers

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Abstract

The topic of clickbait has garnered lot of attention since the advent of social media. Meriam-Webster defines Clickbait as something designed to make readers want to click on a hyperlink especially when the link leads to content of dubious value or interest. Clickbait is used synonymously with terms with negative connotations such as yellow journalism [1], tabloid news etc. Majority of the work in this area has focused on detecting clickbait to stop being presented to the reader. In this work, we look at clickbait in the field of education with emphasis on educational videos that are authored by individual authors without any institutional backing. Such videos can become quite popular with different audiences and are not verified by any expert. We present findings that despite the negative connotation associated with clickbait, the audience value content regardless of the clickbait techniques and have an overall favorable impression. We also establish initial metrics that can be used to gauge the likeness factor for such educational videos/MOOCs.

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Correspondence to Adil E. Rajput .

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Rajput, A.E. (2019). Clickbait in Education—Positive or Negative? Machine Learning Answers. In: Visvizi, A., Lytras, M. (eds) Research & Innovation Forum 2019. RIIFORUM 2019. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-30809-4_10

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  • DOI: https://doi.org/10.1007/978-3-030-30809-4_10

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  • Online ISBN: 978-3-030-30809-4

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