The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Main-memory triangle computations for very large (sparse (power-law)) graphs
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Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
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
Rayward-Smith, V. J. (1991) · Journal of the Operational Research Society · doi:10.1057/jors.1991.155 · Cited by 16,821
Network motifs: simple building blocks of complex networks.
Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002) · Science · doi:10.1126/science.298.5594.824 · Cited by 7,368
Graphs over time: densification laws, shrinking diameters and possible explanations
Leskovec, J., Kleinberg, J., & Faloutsos, C. (2005) · Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining · doi:10.1145/1081870.1081893 · Cited by 2,281
Matrix multiplication via arithmetic progressions
Coppersmith, D., & Winograd, S. (1990) · Journal of Symbolic Computation · doi:10.1016/s0747-7171(08)80013-2 · Cited by 2,248
Introduction to Algorithms, Second Edition
Rivest, R. L., Leiserson, C. E., Cormen, T. H., & Stein, C. (2001) · Cited by 1,984
Breakdown of the Internet under Intentional Attack
Cohen, R., Erez, K., ben-Avraham, D., & Havlin, S. (2001) · Physical Review Letters · doi:10.1103/physrevlett.86.3682 · Cited by 1,455
Pajek - Program for Large Network Analysis
Batagelj, V., & Mrvar, A. (1999) · Cited by 1,414
The webgraph framework I: compression techniques
Boldi, P., & Vigna, S. (2004) · Proceedings of the 13th international conference on World Wide Web · doi:10.1145/988672.988752 · Cited by 1,201
Cited by
On the impact of emotions on author profiling
Rangel, F., & Rosso, P. (2016) · Information Processing & Management · doi:10.1016/j.ipm.2015.06.003 · Cited by 92
Ideological biases in social sharing of online information about climate change
Cann, T. J. B., Weaver, I. S., & Williams, H. T. P. (2021) · PLOS ONE · doi:10.1371/journal.pone.0250656 · Cited by 38
Keerthipriya, P., Nandini, S., & Vidya, T. N. C. (2021) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2021.616666 · Cited by 27
Disrupting networks of hate: characterising hateful networks and removing critical nodes
Alorainy, W., Burnap, P., Liu, H., Williams, M., & Giommoni, L. (2022) · Social Network Analysis and Mining · doi:10.1007/s13278-021-00818-z · Cited by 15
Castillo-de-Mesa, J., Méndez-Domínguez, P., Carbonero-Muñoz, D., & Gómez-Jacinto, L. (2021) · Redes. Revista hispana para el análisis de redes sociales · doi:10.5565/rev/redes.913 · Cited by 13
Metadata
- Authors
- Latapy, M.
- Venue
- Theoretical Computer Science
- Publisher
- Elsevier BV
- Published
- 2008-11
- Volume
- 407
- Issue
- 1-3
- Pages
- 458-473
- ISSN
- 0304-3975 (ISSN-L)
- OpenAlex
- W2016311778
- Cited by
- 458
- References
- 31
- FWCI
- 10.98
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Latapy, M. (2008). Main-memory triangle computations for very large (sparse (power-law)) graphs. Theoretical Computer Science. https://doi.org/10.1016/j.tcs.2008.07.017
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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.
