1. Entropy Measures of Human Communication Dynamics
- Author
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Boleslaw K. Szymanski, Radosław Michalski, Marcin Kulisiewicz, and Przemysław Kazienko
- Subjects
FOS: Computer and information sciences ,Physics - Physics and Society ,Theoretical computer science ,Databases, Factual ,Entropy ,FOS: Physical sciences ,lcsh:Medicine ,Physics and Society (physics.soc-ph) ,01 natural sciences ,Article ,010305 fluids & plasmas ,Social Networking ,0103 physical sciences ,Entropy (information theory) ,Humans ,Interpersonal Relations ,Uniqueness ,010306 general physics ,Students ,lcsh:Science ,Human communication ,Social and Information Networks (cs.SI) ,Physician-Patient Relations ,Text Messaging ,Multidisciplinary ,Social network ,Electronic Mail ,business.industry ,Communication ,lcsh:R ,Computer Science - Social and Information Networks ,Models, Theoretical ,Group Processes ,Optimal distinctiveness theory ,lcsh:Q ,Hospital Communication Systems ,business - Abstract
Human communication is commonly represented as a temporal social network, and evaluated in terms of its uniqueness. We propose a set of new entropy-based measures for human communication dynamics represented within the temporal social network as event sequences. Using real world datasets and random interaction series of different types we find that real human contact events always significantly differ from random ones. This human distinctiveness increases over time and by means of the proposed entropy measures, we can observe sociological processes that take place within dynamic communities.
- Published
- 2018
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