Morningness–eveningness assessment from mobile phone communication analysis

Abstract

Human behaviour follows a 24-h rhythm and is known to be governed by the individual chronotypes. Due to the widespread use of technology in our daily lives, it is possible to record the activities of individuals through their different digital traces. In the present study we utilise a large mobile phone communication dataset containing time stamps of calls and text messages to study the circadian rhythms of anonymous users in a European country. After removing the effect of the synchronization of East-West sun progression with the calling activity, we used two closely related approaches to heuristically compute the chronotypes of the individuals in the dataset, to identify them as morning persons or “larks” and evening persons or “owls”. Using the computed chronotypes we showed how the chronotype is largely dependent on age with younger cohorts being more likely to be owls than older cohorts. Moreover, our analysis showed how on average females have distinctly different chronotypes from males. Younger females are more larkish than males while older females are more owlish. Finally, we also studied the period of low calling activity for each of the users which is considered as a marker of their sleep period during the night. We found that while “extreme larks” tend to sleep more than “extreme owls” on the weekends, we do not observe much variation between them on weekdays. In addition, we have observed that women tend to sleep even less than males on weekdays while there is not much difference between them on the weekends.

Turnover in close friendships

“…We compare these turnovers with respect to different types of relationships. Analysing communication patterns through such mobile phone datasets is a valuable way to gain insight into the social networks of humans 3,11,12 along with their behavioural patterns caused by seasonal and geographical changes 4,13 , daily rhythms [14][15][16] and mobility patterns 17,18 among others 7,[19][20][21] .Human social networks have a layered structure, defined by the fractal structure of the Dunbar number 22 . This fractal structure forms a series of layers in the network that reflect the emotional closeness of the individuals involved [23][24][25][26] .…”

“…We compare these turnovers with respect to different types of relationships. Analysing communication patterns through such mobile phone datasets is a valuable way to gain insight into the social networks of humans 3,11,12 along with their behavioural patterns caused by seasonal and geographical changes 4,13 , daily rhythms [14][15][16] and mobility patterns 17,18 among others 7,[19][20][21] .…”

On the Neurobiological Basis of Chronotype: Insights from a Multimodal Population Neuroscience Study

“…The widespread use of handheld electronic devices, such as smartphones and tablet computers, had a particularly transformative effect, inadvertently delaying people's sleep timing and changing social dynamics [23][24][25] . In summary, as an important construct of relevance to circadian rhythm, chronotype has profound impact on health, habits, and routines that affect each of us every day [26][27][28][29] .…”

Turnover in close friendships: age and gender differences

“…behavioural patterns caused by seasonal and geographical changes 3,26 , daily rhythms [27][28][29] and mobility patterns 30,31 among others 6,23 . A higher calling activity among a pair of individuals can be reasonably assumed to indicate a close relationship between them while a lower calling activity would indicate a weak tie.…”