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 has been a mystery. This paper traces information-spreading processes at a person-by-person level using methods to reconstruct the propagation of massively circulated Internet chain letters. The finding is 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.
[These] chain letters had a type of stroboscopic effect, serving to briefly "light up" a structure - the global e-mail network - that has otherwise been largely invisible, and allowing us to observe a snapshot of this network's everyday use as a means of conveying information. The resulting analysis has exposed several themes. First, accurately reconstructing the paths followed by the information is a computational challenge in itself, given the extensive ways in which the data are mutated as they spread. Second, the spreading patterns of the real chain letters are strongly at odds with the predictions of simpler theoretical models, which posit processes that reach many more people in radically fewer steps. Finally, simple probabilistic models incorporating the speed with which individuals respond to information can produce synthetic spreading patterns that closely resemble the ones we observe in real life.
Tracing information flow on a global scale using Internet chain-letter data
PNAS USA March 19, 2008