Systemic States of Spreading Activation in Describing Associative Knowledge Networks: From Key Items to Relative Entropy Based Comparisons

Associative knowledge networks are central in many areas of learning and teaching. One key problem in evaluating and exploring such networks is to find out its key items (nodes), sub-structures (connected set of nodes), and how the roles of sub-structures can be compared. In this study, we suggest a...

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Main Author: Ismo T. Koponen
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Systems
Subjects:
Online Access:https://www.mdpi.com/2079-8954/9/1/1
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author Ismo T. Koponen
author_facet Ismo T. Koponen
author_sort Ismo T. Koponen
collection DOAJ
description Associative knowledge networks are central in many areas of learning and teaching. One key problem in evaluating and exploring such networks is to find out its key items (nodes), sub-structures (connected set of nodes), and how the roles of sub-structures can be compared. In this study, we suggest an approach for analyzing associative networks, so that analysis is based on spreading activation and systemic states that correpond to the state of spreading. The method is based on the construction of diffusion-propagators as generalized systemic states of the network, for an exploration of the connectivity of a network and, subsequently, on generalized Jensen–Shannon–Tsallis relative entropy (based on Tsallis-entropy) in order to compare the states. It is shown that the constructed systemic states provide a robust way to compare roles of sub-networks in spreading activation. The viability of the method is demonstrated by applying it to recently published network representations of students’ associative knowledge regarding the history of science.
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spelling doaj.art-3647c0daaf8441de83647e115c9415df2022-12-22T04:05:22ZengMDPI AGSystems2079-89542020-12-0191110.3390/systems9010001Systemic States of Spreading Activation in Describing Associative Knowledge Networks: From Key Items to Relative Entropy Based ComparisonsIsmo T. Koponen0Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, FinlandAssociative knowledge networks are central in many areas of learning and teaching. One key problem in evaluating and exploring such networks is to find out its key items (nodes), sub-structures (connected set of nodes), and how the roles of sub-structures can be compared. In this study, we suggest an approach for analyzing associative networks, so that analysis is based on spreading activation and systemic states that correpond to the state of spreading. The method is based on the construction of diffusion-propagators as generalized systemic states of the network, for an exploration of the connectivity of a network and, subsequently, on generalized Jensen–Shannon–Tsallis relative entropy (based on Tsallis-entropy) in order to compare the states. It is shown that the constructed systemic states provide a robust way to compare roles of sub-networks in spreading activation. The viability of the method is demonstrated by applying it to recently published network representations of students’ associative knowledge regarding the history of science.https://www.mdpi.com/2079-8954/9/1/1systemic statesassociative knowledgenetworksdiffusion propagator
spellingShingle Ismo T. Koponen
Systemic States of Spreading Activation in Describing Associative Knowledge Networks: From Key Items to Relative Entropy Based Comparisons
Systems
systemic states
associative knowledge
networks
diffusion propagator
title Systemic States of Spreading Activation in Describing Associative Knowledge Networks: From Key Items to Relative Entropy Based Comparisons
title_full Systemic States of Spreading Activation in Describing Associative Knowledge Networks: From Key Items to Relative Entropy Based Comparisons
title_fullStr Systemic States of Spreading Activation in Describing Associative Knowledge Networks: From Key Items to Relative Entropy Based Comparisons
title_full_unstemmed Systemic States of Spreading Activation in Describing Associative Knowledge Networks: From Key Items to Relative Entropy Based Comparisons
title_short Systemic States of Spreading Activation in Describing Associative Knowledge Networks: From Key Items to Relative Entropy Based Comparisons
title_sort systemic states of spreading activation in describing associative knowledge networks from key items to relative entropy based comparisons
topic systemic states
associative knowledge
networks
diffusion propagator
url https://www.mdpi.com/2079-8954/9/1/1
work_keys_str_mv AT ismotkoponen systemicstatesofspreadingactivationindescribingassociativeknowledgenetworksfromkeyitemstorelativeentropybasedcomparisons