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- Publisher Website: 10.1103/PhysRevE.99.012320
- Scopus: eid_2-s2.0-85060776372
- PMID: 30780212
- WOS: WOS:000456293100009
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Article: Balance in signed networks
Title | Balance in signed networks |
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Authors | |
Issue Date | 2019 |
Citation | Physical Review E, 2019, v. 99, n. 1, article no. 012320 How to Cite? |
Abstract | We consider signed networks in which connections or edges can be either positive (friendship, trust, alliance) or negative (dislike, distrust, conflict). Early literature in graph theory theorized that such networks should display "structural balance," meaning that certain configurations of positive and negative edges are favored and others are disfavored. Here we propose two measures of balance in signed networks based on the established notions of weak and strong balance, and we compare their performance on a range of tasks with each other and with previously proposed measures. In particular, we ask whether real-world signed networks are significantly balanced by these measures compared to an appropriate null model, finding that indeed they are, by all the measures studied. We also test our ability to predict unknown signs in otherwise known networks by maximizing balance. In a series of cross-validation tests we find that our measures are able to predict signs substantially better than chance. |
Persistent Identifier | http://hdl.handle.net/10722/317078 |
ISSN | 2023 Impact Factor: 2.2 2023 SCImago Journal Rankings: 0.805 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Kirkley, Alec | - |
dc.contributor.author | Cantwell, George T. | - |
dc.contributor.author | Newman, M. E.J. | - |
dc.date.accessioned | 2022-09-19T06:18:45Z | - |
dc.date.available | 2022-09-19T06:18:45Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Physical Review E, 2019, v. 99, n. 1, article no. 012320 | - |
dc.identifier.issn | 2470-0045 | - |
dc.identifier.uri | http://hdl.handle.net/10722/317078 | - |
dc.description.abstract | We consider signed networks in which connections or edges can be either positive (friendship, trust, alliance) or negative (dislike, distrust, conflict). Early literature in graph theory theorized that such networks should display "structural balance," meaning that certain configurations of positive and negative edges are favored and others are disfavored. Here we propose two measures of balance in signed networks based on the established notions of weak and strong balance, and we compare their performance on a range of tasks with each other and with previously proposed measures. In particular, we ask whether real-world signed networks are significantly balanced by these measures compared to an appropriate null model, finding that indeed they are, by all the measures studied. We also test our ability to predict unknown signs in otherwise known networks by maximizing balance. In a series of cross-validation tests we find that our measures are able to predict signs substantially better than chance. | - |
dc.language | eng | - |
dc.relation.ispartof | Physical Review E | - |
dc.title | Balance in signed networks | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1103/PhysRevE.99.012320 | - |
dc.identifier.pmid | 30780212 | - |
dc.identifier.scopus | eid_2-s2.0-85060776372 | - |
dc.identifier.volume | 99 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | article no. 012320 | - |
dc.identifier.epage | article no. 012320 | - |
dc.identifier.eissn | 2470-0053 | - |
dc.identifier.isi | WOS:000456293100009 | - |