Difference in communication systems explained by balance between edge and node activations

Abstract

The trade-off between the number of friendships and the closeness of friendships of humans arises due to the limitations of time and cognitive capacities for communication. This trade-off distinguishes asynchronous text communication through the internet (lightweight communication) from face-to-face communication and the social grooming of primates (elaborate communication). This study modelled communication as messaging flows driven by edge and node activations to investigate micro-mechanisms that realise the trade-off law and the differences between the two types of communications. We observed the emergence of five patterns of social structures depending on the strengths of the two types of activations, namely, edge and node activations. The two patterns that show known statistics on empirical studies, such as the trade-off and power-law distributions of closeness, emerged around a threshold between elaborate and lightweight communications, where network structures qualitatively changed. A balance between edge and node activations shifts one pattern (elaborate communication) to another pattern (lightweight communication). Consequently, relation networks that communicate through lightweight communication become less clustered. These results suggest how communication systems construct different social structures, e.g., the impact of popularising the internet.

Synchronization of online social rhythms via avatar communications

“…These dynamics have typically been studied as temporal communication networks based on detailed communication events, e.g. sending messages [12,[22][23][24][25][26]. In contrast, our approach of modeling and analyzing communicating users as coupled oscillators in a social network provided some novel insight from a different perspective.…”

“…These macroscopic behaviors describe population strategies such as role allotment and social coordination in the population.Human communication dynamics are typically modeled as temporal networks, e.g. [12,17,[22][23][24][25][26]. These dynamics include circadian and social rhythms [12,24].…”

“…Human communication dynamics are typically modeled as temporal networks, e.g. [12,17,[22][23][24][25][26]. These dynamics include circadian and social rhythms [12,24].…”

Online Social Support via Avatar Communication Buffers Harmful Effects of Offline Bullying Victimization

“…Social networks composed of elaborate communication methods, e.g., face-to-face communication, have higher cluster coefficients than those consisting of light communication methods, e.g., e-mail and social media (Takano and Nakazato 2021) This finding suggests that application providers can improve social support between players to enhance their mental health via intervention in players' social relationships, e.g., by friend recommendations.…”