High-Modularity Network Generation Model Based on the Muitilayer Network Article Swipe
Many models synthesize various types of complex networks with communities. However, a network generation model that can represent high-modularity networks is rare. In this paper, we propose a high-modularity network generation model by layer aggregation based on a multilayer network. Because people belong to many communities in society, such as family, school, hobby group, and business organizations, each example is regarded as a community in a single layer of a multilayer network. However, measuring each relationship in each community is difficult. A network on social network services (SNSs) that can be observed combines all communities. That is, a social network is generated from a multilayer network. A synthesized network in our model has either a community structure or a high-modularity structure. We apply the proposed model to generate a number of networks and compare them with real-world networks. Not only did it successfully represent real-world networks but we also found that we can predict how real-world networks are generated from the model's parameters.
Related Topics
Concepts
Modularity (biology)
Computer science
Network formation
Evolving networks
Complex network
Network architecture
Network model
Social network (sociolinguistics)
Community structure
Network simulation
Hobby
Layer (electronics)
Distributed computing
Organizational network analysis
Artificial intelligence
Data science
Computer network
World Wide Web
Knowledge management
Social media
Combinatorics
Law
Organic chemistry
Chemistry
Mathematics
Genetics
Political science
Biology
Organizational learning
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1527/tjsai.b-h42
- https://www.jstage.jst.go.jp/article/tjsai/32/6/32_B-H42/_pdf
- OA Status
- diamond
- Cited By
- 3
- References
- 25
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2766341640
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2766341640Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1527/tjsai.b-h42Digital Object Identifier
- Title
-
High-Modularity Network Generation Model Based on the Muitilayer NetworkWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2017Year of publication
- Publication date
-
2017-01-01Full publication date if available
- Authors
-
Chao Fan, Fujio ToriumiList of authors in order
- Landing page
-
https://doi.org/10.1527/tjsai.b-h42Publisher landing page
- PDF URL
-
https://www.jstage.jst.go.jp/article/tjsai/32/6/32_B-H42/_pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://www.jstage.jst.go.jp/article/tjsai/32/6/32_B-H42/_pdfDirect OA link when available
- Concepts
-
Modularity (biology), Computer science, Network formation, Evolving networks, Complex network, Network architecture, Network model, Social network (sociolinguistics), Community structure, Network simulation, Hobby, Layer (electronics), Distributed computing, Organizational network analysis, Artificial intelligence, Data science, Computer network, World Wide Web, Knowledge management, Social media, Combinatorics, Law, Organic chemistry, Chemistry, Mathematics, Genetics, Political science, Biology, Organizational learningTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2022: 1, 2021: 2Per-year citation counts (last 5 years)
- References (count)
-
25Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_date | 2017-01-01 |
| publication_year | 2017 |
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