Mechanisms and architectures of online learning communities

Reuven Aviv, Zippy Erlich, Gilad Ravid

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Online communities are described in terms of collections of virtual neighborhoods, each of which is a sub-set of interdependent members. The significant virtual neighborhoods are revealed by fitting parametric Markov Field models (p*) to the response relations of the communities. The underlying theoretical mechanisms are then deduced by matching the revealed virtual neighborhoods with the predictions of network emergence theories. We demonstrate that the underlying mechanisms are related to specific design features of the communities. This method can be extended to other relations in online communities and to longitudinal analysis, and applied to real-time monitoring of online communications.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Advanced Learning Technologies, ICALT 2004
Editors Kinshuk, C.-K. Looi, E. Sutinen, D. Sampson, I. Aedo, L. Uden, E. Kaehkoenen
Pages400-404
Number of pages5
DOIs
StatePublished - 1 Dec 2004
Externally publishedYes
EventProceedings - IEEE International Conference on Advanced Learning Technologies, ICALT 2004 - Joensuu, Finland
Duration: 30 Aug 20041 Sep 2004

Conference

ConferenceProceedings - IEEE International Conference on Advanced Learning Technologies, ICALT 2004
Country/TerritoryFinland
CityJoensuu
Period30/08/041/09/04

ASJC Scopus subject areas

  • General Engineering

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