An Unsupervised Approach to User Characterization in Online Learning and Social Platforms

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Making sense of data that is automatically collected from online platforms such as online social media or e-learning platforms is a challenging task: the data is massive, multidimensional, noisy, and heterogeneous (composed of differently behaving individuals). In this chapter we focus on a central task common to all on-line social platforms and that is the task of user characterization. For example, automatically identify a spammer or a bot on Twitter, or a disengaged student in an e-learning platform.
Original languageAmerican English
Title of host publicationMathematics (Education) in the Information Age
EditorsS.A. Costa, M. Danesi, D. Martinovic
Place of PublicationCham
PublisherSpringer
Pages15-36
Number of pages22
ISBN (Electronic)978-3-030-59177-9
ISBN (Print)978-3-030-59176-2
DOIs
StatePublished - 11 Dec 2020

Publication series

NameMathematics in Mind
PublisherSpringer

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