We illustrate a simple model of knowledge scaffolding, based on the process of building a corpus of knowledge, each item of which is linked to “previous” ones. The basic idea is that the relationships among the items of corpus can be essentially drawn as an acyclic network, in which topmost contributions are “derived” from items at lower levels. When a new item is added to the corpus, we impose a limit to the maximum unit increase (i.e., “jumps”) of knowledge. We analyzed the time growth of the corpus (number of items) and the maximum knowledge, both showing a power law. Another result was that the number of “holes” in the knowledge corpus always remains limited. Our model can be used as a rough approximation to the asymptotic growth of Wikipedia, and indeed, actual data show a certain resemblance with our model. Assuming that the user base is growing, at beginning, in an exponential way, one can also recover the early phases of Wikipedia growth.

A Simple Model of Knowledge Scaffolding Applied to Wikipedia Growth / Bagnoli F.; de Bonfioli Cavalcabo' G.. - In: FUTURE INTERNET. - ISSN 1999-5903. - ELETTRONICO. - 15:(2023), pp. 67.1-67.14. [10.3390/fi15020067]

A Simple Model of Knowledge Scaffolding Applied to Wikipedia Growth

Bagnoli F.
Writing – Original Draft Preparation
;
de Bonfioli Cavalcabo' G.
Writing – Review & Editing
2023

Abstract

We illustrate a simple model of knowledge scaffolding, based on the process of building a corpus of knowledge, each item of which is linked to “previous” ones. The basic idea is that the relationships among the items of corpus can be essentially drawn as an acyclic network, in which topmost contributions are “derived” from items at lower levels. When a new item is added to the corpus, we impose a limit to the maximum unit increase (i.e., “jumps”) of knowledge. We analyzed the time growth of the corpus (number of items) and the maximum knowledge, both showing a power law. Another result was that the number of “holes” in the knowledge corpus always remains limited. Our model can be used as a rough approximation to the asymptotic growth of Wikipedia, and indeed, actual data show a certain resemblance with our model. Assuming that the user base is growing, at beginning, in an exponential way, one can also recover the early phases of Wikipedia growth.
2023
15
1
14
Goal 4: Quality education
Bagnoli F.; de Bonfioli Cavalcabo' G.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1301662
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