The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Identifying and ranking influential spreaders in complex networks by neighborhood coreness
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135
Statistical mechanics of complex networks
Albert, R., & Barabási, A.-L. (2002) · Reviews of Modern Physics · doi:10.1103/revmodphys.74.47 · Cited by 20,471
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Error and attack tolerance of complex networks
Albert, R., Jeong, H., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35019019 · Cited by 7,534
Error and attack tolerance of complex networksPreprint
Albert, R., Jeong, H., & Barabási, A.-Ĺ. (2000) · Cited by 6,467
Epidemic Spreading in Scale-Free Networks
Pastor-Satorras, R., & Vespignani, A. (2001) · Physical Review Letters · doi:10.1103/physrevlett.86.3200 · Cited by 5,731
Finding community structure in networks using the eigenvectors of matrices
Newman, M. E. J. (2006) · Physical Review E · doi:10.1103/physreve.74.036104 · Cited by 4,761
An Information Flow Model for Conflict and Fission in Small Groups
Zachary, W. W. (1977) · Journal of Anthropological Research · doi:10.1086/jar.33.4.3629752 · Cited by 4,704
Spread of epidemic disease on networks
Newman, M. E. J. (2002) · Physical Review E · doi:10.1103/physreve.66.016128 · Cited by 3,218
Cited by
Identifying influential spreaders in complex networks based on gravity formula
Ma, L.-L., Ma, C., Zhang, H.-F., & Wang, B.-H. (2016) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2015.12.162 · Cited by 367
Deep Recursive Network Embedding with Regular Equivalence
Tu, K., Cui, P., Wang, X., Yu, P. S., & Zhu, W. (2018) · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining · doi:10.1145/3219819.3220068 · Cited by 179
Metadata
- Authors
- Bae, J., & Kim, S.
- Venue
- Physica A: Statistical Mechanics and its Applications
- Publisher
- Elsevier BV
- Published
- 2014-02
- Volume
- 395
- Pages
- 549-559
- ISSN
- 0378-4371 (ISSN-L)
- OpenAlex
- W2040763707
- Cited by
- 564
- References
- 39
- FWCI
- 9.57
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Identifying and ranking influential spreaders in complex networks by neighborhood coreness. https://app.cochat.ai/papers/10.1016/j.physa.2013.10.047
- The paper
- Bae, J., & Kim, S. (2014). Identifying and ranking influential spreaders in complex networks by neighborhood coreness. Physica A: Statistical Mechanics and its Applications. https://doi.org/10.1016/j.physa.2013.10.047
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
