Dynamics of social balance under temporal interaction

Nishi, Ryosuke; Masuda, Naoki

doi:10.1209/0295-5075/107/48003

Cited by 17 publications

(11 citation statements)

References 40 publications

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“…In fact, effects of temporal networks on collective dynamics have been investigated with various models 3 . Examples include nonlinear coupled dynamics towards synchronisation 4 , the voter model 6 7 8 , the naming game 9 10 , the information cascade model 11 , dynamics of triangular social balance 12 , evolutionary game dynamics 13 , and, above all, epidemic processes 14 15 . The link order may add another dimension to the impact of temporal networks on these and other dynamics.…”

Section: Discussionmentioning

confidence: 99%

Accelerating coordination in temporal networks by engineering the link order

Masuda¹

2016

Sci Rep

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Social dynamics on a network may be accelerated or decelerated depending on which pairs of individuals in the network communicate early and which pairs do later. The order with which the links in a given network are sequentially used, which we call the link order, may be a strong determinant of dynamical behaviour on networks, potentially adding a new dimension to effects of temporal networks relative to static networks. Here we study the effect of the link order on linear coordination (i.e., synchronisation) dynamics. We show that the coordination speed considerably depends on specific orders of links. In addition, applying each single link for a long time to ensure strong pairwise coordination before moving to a next pair of individuals does not often enhance coordination of the entire network. We also implement a simple greedy algorithm to optimise the link order in favour of fast coordination.

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Section: Discussionmentioning

confidence: 99%

Accelerating coordination in temporal networks by engineering the link order

Masuda¹

2016

Sci Rep

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“…Comparing the voter model to other dynamic models on empirical data sets would be interesting. Nishi and Masuda [210] study another model of opinion spreading based on social balance theory. This theory con-cerns networks with both positive and negative links.…”

Section: Opinion and Information Spreadingmentioning

confidence: 99%

Modern temporal network theory: a colloquium

2015

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Abstract. The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.

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“…A similar absorbing phase transition in friendship and enmity networks was observed in Heider's structural balance models [10][11][12][13][14][15][16][17][18][19][20]. The structural balance models assume that agents either mutually like or dislike each other and change their opinion to increase their triad balance.…”

Section: By Solving Dmentioning

confidence: 54%

Balanced-imbalanced transitions in indirect reciprocity dynamics on networks

et al. 2021

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Here we investigate the dynamics of indirect reciprocity on networks, a type of social dynamics in which the attitude of individuals, either cooperative or antagonistic, toward other individuals changes over time based upon their actions and mutual monitoring. We observe an absorbing state phase transition as we change the network's link or edge density. When the edge density is either small or large enough, opinions quickly reach an absorbing state, from which opinions never change anymore once reached. In contrast, if the edge density is in the middle range, the absorbing state is not reached and the state keeps changing, thus being active. The result shows an effect of social networks on spontaneous group formation.

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Dynamics of social balance under temporal interaction

Cited by 17 publications

References 40 publications

Accelerating coordination in temporal networks by engineering the link order

Accelerating coordination in temporal networks by engineering the link order

Modern temporal network theory: a colloquium

Balanced-imbalanced transitions in indirect reciprocity dynamics on networks

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