Lognormal Infection Times of Online Information Spread

Abstract

The infection times of individuals in online information spread such as the inter-arrival time of Twitter messages or the propagation time of news stories on a social media site can be explained through a convolution of lognormally distributed observation and reaction times of the individual participants. Experimental measurements support the lognormal shape of the individual contributing processes, and have resemblance to previously reported lognormal distributions of human behavior and contagious processes.

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• Emergence of Blind Areas in Information Spreading
• Stability of SIS Spreading Processes in Networks with Non-Markovian Transmission and Recovery
• The Economy of Internet-Based Hospitality Exchange
• Spreading Processes over Socio-Technical Networks with Phase-Type Transmissions