Abstract
Although information, news, and opinions continuously circulate in the worldwide social network, the actual mechanics of how any single piece of information spreads on a global scale have been a mystery. Here, we trace such information-spreading processes at a person-by-person level using methods to reconstruct the propagation of massively circulated Internet chain letters. We find that rather than fanning out widely, reaching many people in very few steps according to “small-world” principles, the progress of these chain letters proceeds in a narrow but very deep tree-like pattern, continuing for several hundred steps. This suggests a new and more complex picture for the spread of information through a social network. We describe a probabilistic model based on network clustering and asynchronous response times that produces trees with this characteristic structure on social-network data.
Keywords
TracingComputer scienceThe InternetTRACE (psycholinguistics)Asynchronous communicationInformation flowProbabilistic logicData scienceCluster analysisScale (ratio)Chain (unit)Social network (sociolinguistics)Social mediaWorld Wide WebArtificial intelligenceGeographyTelecommunicationsCartography
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Publication Info
- Year
- 2008
- Type
- article
- Volume
- 105
- Issue
- 12
- Pages
- 4633-4638
- Citations
- 418
- Access
- Closed
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Cite This
David Liben‐Nowell,
Jon Kleinberg
(2008).
Tracing information flow on a global scale using Internet chain-letter data.
Proceedings of the National Academy of Sciences
, 105
(12)
, 4633-4638.
https://doi.org/10.1073/pnas.0708471105
Identifiers
- DOI
- 10.1073/pnas.0708471105