The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Social influence analysis in large-scale networks
Abstract
In large social networks, nodes (users, entities) are influenced by others for various reasons. For example, the colleagues have strong influence on one's work, while the friends have strong influence on one's daily life. How to differentiate the social influences from different angles(topics)? How to quantify the strength of those social influences? How to estimate the model on real large networks?
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Cites
Granovetter, M. S. (1973) · American Journal of Sociology · doi:10.1086/225469 · Cited by 40,491
(2003) · Journal of Machine Learning Research · doi:10.5555/944919.944937 · Cited by 32,337
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
The Structure and Function of Complex Networks
Newman, M. E. J. (2003) · SIAM Review · doi:10.1137/s003614450342480 · Cited by 18,719
Social Network Analysis: Methods and Applications
Wasserman, S. S., & Faust, K. (1994) · Cited by 17,961
Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. (1994) · doi:10.1017/cbo9780511815478 · Cited by 17,557
Strogatz, S. H. (2001) · Nature · doi:10.1038/35065725 · Cited by 8,302
Factor graphs and the sum-product algorithm
Kschischang, F. R., Frey, B. J., & Loeliger, H.-A. (2001) · IEEE Transactions on Information Theory · doi:10.1109/18.910572 · Cited by 6,486 · cited 3×
“The approach is based on the theory of factor graph [17], in which the observation data are cohesive on both local attributes and relationships.”
MethodOn power-law relationships of the Internet topology
Faloutsos, M., Faloutsos, P., & Faloutsos, C. (1999) · Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication · doi:10.1145/316188.316229 · Cited by 4,196
Probabilistic Latent Semantic Indexing
Hofmann, T. (2017) · ACM SIGIR Forum · doi:10.1145/3130348.3130370 · Cited by 3,988
Cited by
Chen, M., Mao, S., & Liu, Y. (2014) · Mobile Networks and Applications · doi:10.1007/s11036-013-0489-0 · Cited by 2,913
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Chen, W., Wang, C., & Wang, Y. (2010) · Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1835804.1835934 · Cited by 1,731
Self-citationToward Scalable Systems for Big Data Analytics: A Technology Tutorial
Hu, H., Wen, Y., Chua, T.-S., & Li, X. (2014) · IEEE Access · doi:10.1109/access.2014.2332453 · Cited by 1,099
Scalable Influence Maximization in Social Networks under the Linear Threshold Model
Chen, W., Yuan, Y., & Zhang, L. (2010) · 2010 IEEE International Conference on Data Mining · doi:10.1109/icdm.2010.118 · Cited by 924
Influence Maximization on Social Graphs: A Survey
Li, Y., Fan, J., Wang, Y., & Tan, K.-L. (2018) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2018.2807843 · Cited by 659
Metadata
- Authors
- Tang, J., Sun, J., Wang, C., & Yang, Z.
- Venue
- Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
- Publisher
- ACM
- Published
- 2009-06-28
- Pages
- 807-816
- OpenAlex
- W2107559689
- Cited by
- 927
- References
- 25
- FWCI
- 39.50
- Type
- conference paper
- Language
- en
- Open access
- closed
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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.