The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Meme-tracking and the dynamics of the news cycle
Abstract
Tracking new topics, ideas, and "memes" across the Web has been an issue of considerable interest. Recent work has developed methods for tracking topic shifts over long time scales, as well as abrupt spikes in the appearance of particular named entities. However, these approaches are less well suited to the identification of content that spreads widely and then fades over time scales on the order of days - the time scale at which we perceive news and events.
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
(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 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
Blei, D. M., & Lafferty, J. D. (2006) · Proceedings of the 23rd international conference on Machine learning - ICML '06 · doi:10.1145/1143844.1143859 · Cited by 2,386
Christoph, V. F., Lazarfeld, P. F., Berelson, B., & Gaudet, H. (1945) · The American Catholic Sociological Review · doi:10.2307/3707538 · Cited by 1,732
Bursty and hierarchical structure in streams
Kleinberg, J. (2002) · Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/775047.775061 · Cited by 1,160
Self-citationTopics over time: a non-Markov continuous-time model of topical trends
Wang, X., & McCallum, A. (2006) · Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1150402.1150450 · Cited by 1,121
Elements of mathematical ecology
(2002) · Choice Reviews Online · doi:10.5860/choice.39-3372 · Cited by 1,081
Elements of Mathematical Ecology
Kot, M. (2001) · Cambridge University Press eBooks · doi:10.1017/cbo9780511608520 · Cited by 1,054
Information diffusion through blogspace
Gruhl, D., Guha, R., Liben-Nowell, D., & Tomkins, A. (2004) · Proceedings of the 13th international conference on World Wide Web · doi:10.1145/988672.988739 · Cited by 1,041
Cited by
What is Twitter, a social network or a news media?
Kwak, H., Lee, C., Park, H., & Moon, S. (2010) · Proceedings of the 19th international conference on World wide web · doi:10.1145/1772690.1772751 · Cited by 6,652
Comparing Twitter and Traditional Media Using Topic Models
Zhao, W. X., Jiang, J., Weng, J., He, J., Lim, E.-P., Yan, H., & Li, X. (2011) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-20161-5_34 · Cited by 1,214
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
Self-citationPatterns 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-citationSNAP: A General-Purpose Network Analysis and Graph-Mining Library
Leskovec, J., & Sosič, R. (2017) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/2898361 · Cited by 870
Self-citation
Metadata
- Authors
- Leskovec, J., Backstrom, L., & Kleinberg, J.
- Venue
- Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
- Publisher
- ACM
- Published
- 2009-06-28
- Pages
- 497-506
- OpenAlex
- W2127492100
- Cited by
- 1,530
- References
- 28
- FWCI
- 73.57
- Type
- conference paper
- 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: Meme-tracking and the dynamics of the news cycle. https://app.cochat.ai/papers/10.1145/1557019.1557077
- The paper
- Leskovec, J., Backstrom, L., & Kleinberg, J. (2009). Meme-tracking and the dynamics of the news cycle. Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining. https://doi.org/10.1145/1557019.1557077
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.
