The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Patterns of Cascading Behavior in Large Blog Graphs
Abstract
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we address in this work. Blogs (weblogs) have become an important medium of information because of their timely publication, ease of use, and wide availability. In fact, they often make headlines, by discussing and discovering evidence about political events and facts. Often blogs link to one another, creating a publicly available record of how information and influence spreads through an underlying social network. Aggregating links from several blog posts creates a directed graph which we analyze to discover the patterns of information propagation in blogspace, and thereby understand the underlying social network. Here we report some surprising findings of the blog linking and information propagation structure, after we analyzed one of the largest available datasets, with 45,000 blogs and ≈ 2.2 million blog-postings. Our analysis also sheds light on how rumors, viruses, and ideas propagate over social and computer networks.
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Cites
The political blogosphere and the 2004 U.S. election: divided they blog
Adamic, L. A., & Glance, N. (2005) · Proceedings of the 3rd international workshop on Link discovery · doi:10.1145/1134271.1134277 · Cited by 2,619
Self-citationThe origin of bursts and heavy tails in human dynamics
Barabási, A.-L. (2005) · Nature · doi:10.1038/nature03459 · Cited by 2,210
Cited by
Epidemic processes in complex networks
Pastor-Satorras, R., Castellano, C., Van Mieghem, P., & Vespignani, A. (2015) · Reviews of Modern Physics · doi:10.1103/revmodphys.87.925 · Cited by 3,697
Romero, D. M., Meeder, B., & Kleinberg, J. (2011) · Proceedings of the 20th international conference on World wide web · doi:10.1145/1963405.1963503 · Cited by 1,082
Patterns of temporal variation in online media
Yang, J., & Leskovec, J. (2011) · Proceedings of the fourth ACM international conference on Web search and data mining · doi:10.1145/1935826.1935863 · Cited by 986
Self-citationInformation diffusion in online social networks: a survey
Guille, A., Hacid, H., Favre, C., & Zighed, D. A. (2013) · ACM SIGMOD Record · doi:10.1145/2503792.2503797 · Cited by 851
Raafat, R. M., Chater, N., & Frith, C. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2009.08.002 · Cited by 479
Metadata
- Authors
- Leskovec, J., McGlohon, M., Faloutsos, C., Glance, N., & Hurst, M.
- Venue
- Proceedings of the 2007 SIAM International Conference on Data Mining
- Published
- 2007-04-26
- Pages
- 551-556
- OpenAlex
- W171462922
- Cited by
- 570
- References
- 2
- FWCI
- 27.20
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Leskovec, J., McGlohon, M., Faloutsos, C., Glance, N., & Hurst, M. (2007). Patterns of Cascading Behavior in Large Blog Graphs. Proceedings of the 2007 SIAM International Conference on Data Mining. https://doi.org/10.1137/1.9781611972771.60
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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.
