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Published on: November 10, 2010
Evidence for a bimodal distribution in human communication
Ye Wu1, Changsong Zhou, Jinghua Xiao
1Potsdam Institute for Climate Impact Research, PO Box 60 12 03, 14412 Potsdam, United Kingdom.
Summary
Human communication events arise from task initiation and interaction, creating unique bimodal interevent time distributions. This finding offers insights into individual and network human activities.
Area of Science:
- Complex systems
- Network science
- Human dynamics
Background:
- Human activities, including social, technological, and economic phenomena, are driven by interacting processes.
- Understanding the underlying mechanisms of these interactions is crucial for modeling complex systems.
Purpose of the Study:
- To empirically investigate the driving forces behind human communication patterns.
- To develop a model explaining the observed interevent time distributions in human interactions.
Main Methods:
- Analysis of Short Message (SMS) correspondence data.
- Development of a minimal model of two interacting priority queues.
- Fitting the model to empirical data and extracting parameters.
Main Results:
- Human actions result from Poisson task initiation and decision-making, plus interpersonal interactions.
- Interevent time distributions are a bimodal combination of Poisson and power-law characteristics.
- Events form independent bursts driven by frequent short-term interactions and random long-term initiations.
Conclusions:
- The interplay of different time scales in human communication generates bimodal activity.
- The developed model accurately captures empirical distributions and can be applied to other communication systems (email, letters).
- Findings provide insights into human activity at individual and network levels and may illuminate bimodal phenomena in other complex systems.
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