Channel-Specific Daily Patterns in Mobile Phone Communication

Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)


Humans follow circadian rhythms, visible in their activity levels as well as physiological and psychological factors. Such rhythms are also visible in electronic communication records, where the aggregated activity levels of e.g. mobile telephone calls or Wikipedia edits are known to follow their own daily patterns. Here, we study the daily communication patterns of 24 individuals over 18 months, and show each individual has a different, persistent communication pattern. These patterns may differ for calls and text messages, which points towards calls and texts serving a different role in communication. For both calls and texts, evenings play a special role. There are also differences in the daily patterns of males and females both for calls and texts, both in how they communicate with individuals of the same gender versus opposite gender, and also in how communication is allocated at social ties of different nature (kin ties vs. non-kin ties). Taken together, our results show that there is an unexpected richness to the daily communication patterns, from different types of ties being activated at different times of day to different roles of channels and gender differences.


Circadian Rhythm Text Message Relative Entropy Reference Distance Daily Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



TA and JS acknowledge support from the Academy of Finland, project “Temporal networks of human interactions” (no. 260427), and computational resources by Aalto Science IT. RD’s research is supported by an ERC Advanced grant. SGBR and RD acknowledge support from the UK EPSRC and ESRC research councils for collecting the data.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Aalto University School of ScienceEspooFinland
  2. 2.CABDyN Complexity Center, Saïd Business SchoolUniversity of OxfordOxfordUK
  3. 3.Department of PsychologyUniversity of ChesterChesterUK
  4. 4.Department of SociologyUniversity of OxfordOxfordUK
  5. 5.Departamento de Matemáticas & GISCUniversidad Carlos III de MadridLeganésSpain
  6. 6.Department of Experimental PsychologyUniversity of OxfordOxfordUK

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