The DOI matches its Crossref record.
Predicting the popularity of online content
Abstract
Early patterns of Digg diggs and YouTube views reflect long-term user interest.
Overview
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Citations
Cited by
Smart Cities: A Survey on Data Management, Security, and Enabling Technologies
Gharaibeh, A., Salahuddin, M. A., Hussini, S. J., Khreishah, A., Khalil, I., Guizani, M., & Al-Fuqaha, A. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2736886 · Cited by 628
SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity
Zhao, Q., Erdogdu, M. A., He, H. Y., Rajaraman, A., & Leskovec, J. (2015) · Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/2783258.2783401 · Cited by 478
A Survey of Information Cascade Analysis: Models, Predictions, and Recent Advances
Zhou, F., Xu, X., Trajcevski, G., & Zhang, K. (2022) · ACM Computing Surveys · doi:10.1145/3433000 · Cited by 259
Diffusion of Scientific Articles across Online Platforms
Zakhlebin, I., & Horvát, E.-Á. (2020) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v14i1.7341 · Cited by 16
“…the structure and dynamics of information diffusion has been a longstanding research problem in communication and media studies (Katz and Lazarsfeld 1955), marketing and management (Aral and Walker 2011), and information science (Szabo and Huberman 2010; Jamali and Rangwala 2009; Weng et al. 2012).”
BackgroundSemantic Image Analysis on Social Networks and Data Processing: Review and Future Directions
Alzboon, M. S., Alqaraleh, M. K., Aljarrah, E. M., & Alomari, S. A. (2022) · Advances in Business Information Systems and Analytics · doi:10.4018/978-1-7998-9016-4.ch009 · Cited by 1
Metadata
- Authors
- Szabo, G., & Huberman, B. A.
- Venue
- Communications of the ACM
- Published
- 2010-08
- Volume
- 53
- Issue
- 8
- Pages
- 80-88
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W3125952634
- Cited by
- 983
- References
- 0
- FWCI
- 41.13
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Predicting the popularity of online content. https://app.cochat.ai/papers/10.1145/1787234.1787254
- The paper
- Szabo, G., & Huberman, B. A. (2010). Predicting the popularity of online content. Communications of the ACM. https://doi.org/10.1145/1787234.1787254
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.
