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 languageEnglish
    Title of host publicationMathematics (Education) in the Information Age
    Editors S.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

    Name Mathematics in Mind
    PublisherSpringer
    ISSN (Print)2522-5405
    ISSN (Electronic)2522-5413

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