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Virtual learning communities (VLCs) rethinking: influence on behavior modification—bullying detection through machine learning and natural language processing

verfasst von: Stefanos Nikiforos, Spyros Tzanavaris, Katia-Lida Kermanidis

Erschienen in: Journal of Computers in Education | Ausgabe 4/2020

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Abstract

The current study attempts to investigate the influence of virtual learning communities (VLCs) on behavior modification, through the bullying paradigm, using natural language processing (NLP) techniques. The key question is whether individual learners that bully in their physical learning community (PLC) can be able to exhibit a behavior modification, if integrated in a VLC. Results indicate that the attempted "integration" could be a promising framework to behavior modification via a virtual community. Furthermore, machine learning is employed for the automatic detection of aggressive behavior that can facilitate the timely teacher's intervention, without him having to manually scan through the textual dataset. To the authors' knowledge, this is the first time such a linguistic and behavioral analysis for bullying detection is applied to VLCs. Another innovative challenge is the language targeted in the analysis, namely Greek.

Vorheriger Artikel Direct or indirect effects from “perceived characteristic of innovation” to “intention to pay”: mediation of continuance intention to use e-learning

Nächster Artikel Learners’ perceptions and experiences of studying psychology online

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Titel: Virtual learning communities (VLCs) rethinking: influence on behavior modification—bullying detection through machine learning and natural language processing
verfasst von: Stefanos Nikiforos
Spyros Tzanavaris
Katia-Lida Kermanidis
Publikationsdatum: 28.05.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Computers in Education / Ausgabe 4/2020
Print ISSN: 2197-9987
Elektronische ISSN: 2197-9995
DOI: https://doi.org/10.1007/s40692-020-00166-5

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