Limits...
Limited communication capacity unveils strategies for human interaction.

Miritello G, Lara R, Cebrian M, Moro E - Sci Rep (2013)

Bottom Line: Contrary to the perception of ever-growing connectivity, we observe that individuals exhibit a finite communication capacity, which limits the number of ties they can maintain active in time.On average men display higher capacity than women, and this capacity decreases for both genders over their lifespan.This allows us to draw novel relationships between individual strategies for human interaction and the evolution of social networks at global scale.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Matemáticas & GISC, Universidad Carlos III de Madrid, 28911 Leganés, Spain.

ABSTRACT
Connectivity is the key process that characterizes the structural and functional properties of social networks. However, the bursty activity of dyadic interactions may hinder the discrimination of inactive ties from large interevent times in active ones. We develop a principled method to detect tie de-activation and apply it to a large longitudinal, cross-sectional communication dataset (≈19 months, ≈20 million people). Contrary to the perception of ever-growing connectivity, we observe that individuals exhibit a finite communication capacity, which limits the number of ties they can maintain active in time. On average men display higher capacity than women, and this capacity decreases for both genders over their lifespan. Separating communication capacity from activity reveals a diverse range of tie activation strategies, from stable to exploratory. This allows us to draw novel relationships between individual strategies for human interaction and the evolution of social networks at global scale.

No MeSH data available.


Communication capacity and evolution of activity.Panel (A) shows the communication events of a given individual in our database with all her neighbors in the observation window Ω.For each tie id, a vertical line represents a call with the corresponding neighbor. Grey horizontal rectangles are drawn from the first to the last observed communication event in each tie, considering also events before and after Ω. Panel (B) shows vertical up/down arrows for each tie activation/deactivation events detected within Ω. Using those events, panel (C) shows the aggregated number of active ties as a function of time κi(0) + nα,i(t) and the aggregated number of deactivated ties nω,i. Dashed line is the apparent growth in the social connectivity ki(t) obtained by the cumulative number of observed activity in ties up to some time, while red line is the number of active connections at a given instant κi(t).
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f2: Communication capacity and evolution of activity.Panel (A) shows the communication events of a given individual in our database with all her neighbors in the observation window Ω.For each tie id, a vertical line represents a call with the corresponding neighbor. Grey horizontal rectangles are drawn from the first to the last observed communication event in each tie, considering also events before and after Ω. Panel (B) shows vertical up/down arrows for each tie activation/deactivation events detected within Ω. Using those events, panel (C) shows the aggregated number of active ties as a function of time κi(0) + nα,i(t) and the aggregated number of deactivated ties nω,i. Dashed line is the apparent growth in the social connectivity ki(t) obtained by the cumulative number of observed activity in ties up to some time, while red line is the number of active connections at a given instant κi(t).

Mentions: The procedure described above allows us to determine the tie activation and deactivation events for each individual along the observation period of 7 months (see Fig. 2). With those events, we build her instantaneous communication capacity κi(t), defined as the number of active ties at any given instant t. In principle, κi(t) is very different from ki(t), the aggregated number of revealed ties up to time t, which is usually what is taken as a proxy for social connectivity23. Because of the bursty nature of interactions, ki(t) has a fictitious nontrivial time dynamics at the beginning of the observation period which is typically ignored in observations (see SI Section 1 for its implications). However, if we aggregate the number of activated (deactivated) ties up to time t, denoted by nα,i(t) [nω,i(t)], we get that at the end of Ω we have ki(T) = κi(0) + nα,i(T). Thus ki(T) is a combination of the communication capacity and communication activity in Ω. In our database we find a large heterogeneity in nα,i(T) and nω,i(T) [see Fig. 3a]: while on average people activate/deactivate about 8 (reciprocated) ties in a period of 7 months, 20% of users in our database activate/deactivate more than 15 ties in that period. Note that on average nα,i(T) and nω,i(T) almost equals ki(T)/2, (see Fig. 3a), which suggests that a large fraction of the revealed aggregated social connectivity ki(T) is given by newly activated or deactivated connections; similar ratio of activation/deactivation is found in the Facebook database (see SI Section 7). Thus, ki(T) usually overestimates the instantaneous human communication capacity of maintaining active social ties.


Limited communication capacity unveils strategies for human interaction.

Miritello G, Lara R, Cebrian M, Moro E - Sci Rep (2013)

Communication capacity and evolution of activity.Panel (A) shows the communication events of a given individual in our database with all her neighbors in the observation window Ω.For each tie id, a vertical line represents a call with the corresponding neighbor. Grey horizontal rectangles are drawn from the first to the last observed communication event in each tie, considering also events before and after Ω. Panel (B) shows vertical up/down arrows for each tie activation/deactivation events detected within Ω. Using those events, panel (C) shows the aggregated number of active ties as a function of time κi(0) + nα,i(t) and the aggregated number of deactivated ties nω,i. Dashed line is the apparent growth in the social connectivity ki(t) obtained by the cumulative number of observed activity in ties up to some time, while red line is the number of active connections at a given instant κi(t).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3674429&req=5

f2: Communication capacity and evolution of activity.Panel (A) shows the communication events of a given individual in our database with all her neighbors in the observation window Ω.For each tie id, a vertical line represents a call with the corresponding neighbor. Grey horizontal rectangles are drawn from the first to the last observed communication event in each tie, considering also events before and after Ω. Panel (B) shows vertical up/down arrows for each tie activation/deactivation events detected within Ω. Using those events, panel (C) shows the aggregated number of active ties as a function of time κi(0) + nα,i(t) and the aggregated number of deactivated ties nω,i. Dashed line is the apparent growth in the social connectivity ki(t) obtained by the cumulative number of observed activity in ties up to some time, while red line is the number of active connections at a given instant κi(t).
Mentions: The procedure described above allows us to determine the tie activation and deactivation events for each individual along the observation period of 7 months (see Fig. 2). With those events, we build her instantaneous communication capacity κi(t), defined as the number of active ties at any given instant t. In principle, κi(t) is very different from ki(t), the aggregated number of revealed ties up to time t, which is usually what is taken as a proxy for social connectivity23. Because of the bursty nature of interactions, ki(t) has a fictitious nontrivial time dynamics at the beginning of the observation period which is typically ignored in observations (see SI Section 1 for its implications). However, if we aggregate the number of activated (deactivated) ties up to time t, denoted by nα,i(t) [nω,i(t)], we get that at the end of Ω we have ki(T) = κi(0) + nα,i(T). Thus ki(T) is a combination of the communication capacity and communication activity in Ω. In our database we find a large heterogeneity in nα,i(T) and nω,i(T) [see Fig. 3a]: while on average people activate/deactivate about 8 (reciprocated) ties in a period of 7 months, 20% of users in our database activate/deactivate more than 15 ties in that period. Note that on average nα,i(T) and nω,i(T) almost equals ki(T)/2, (see Fig. 3a), which suggests that a large fraction of the revealed aggregated social connectivity ki(T) is given by newly activated or deactivated connections; similar ratio of activation/deactivation is found in the Facebook database (see SI Section 7). Thus, ki(T) usually overestimates the instantaneous human communication capacity of maintaining active social ties.

Bottom Line: Contrary to the perception of ever-growing connectivity, we observe that individuals exhibit a finite communication capacity, which limits the number of ties they can maintain active in time.On average men display higher capacity than women, and this capacity decreases for both genders over their lifespan.This allows us to draw novel relationships between individual strategies for human interaction and the evolution of social networks at global scale.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Matemáticas & GISC, Universidad Carlos III de Madrid, 28911 Leganés, Spain.

ABSTRACT
Connectivity is the key process that characterizes the structural and functional properties of social networks. However, the bursty activity of dyadic interactions may hinder the discrimination of inactive ties from large interevent times in active ones. We develop a principled method to detect tie de-activation and apply it to a large longitudinal, cross-sectional communication dataset (≈19 months, ≈20 million people). Contrary to the perception of ever-growing connectivity, we observe that individuals exhibit a finite communication capacity, which limits the number of ties they can maintain active in time. On average men display higher capacity than women, and this capacity decreases for both genders over their lifespan. Separating communication capacity from activity reveals a diverse range of tie activation strategies, from stable to exploratory. This allows us to draw novel relationships between individual strategies for human interaction and the evolution of social networks at global scale.

No MeSH data available.