We investigated the structure and seasonality of the proximity network in a group of polygynous western black crested gibbons (Nomascus concolor) using social network analysis. The spatial proximity changed seasonally...We investigated the structure and seasonality of the proximity network in a group of polygynous western black crested gibbons (Nomascus concolor) using social network analysis. The spatial proximity changed seasonally and was affected by temperature and rainfall. Preferred proximity association was not distributed randomly among individuals. Kinship was one explanation for the social structure, as offspring preferred to maintain close proximity with their mothers. The proximity of infants to mothers decreased with age, and independent offspring had lower proximity to mothers than dependent ones. We found that the adult male had different proximity relationships with two different adult females. The frequency of proximity between the male and the infant-carrying female was significantly higher than that between the male and the female who had immigrated carrying one offspring of uncertain paternity into the group. Infanticide avoidance and/or predation protection for dependent infants might explain the proximity relationship differences. Temperature influenced group proximity association, with individual proximity increasing in the cold months and decreasing in the hot months. Group proximity decreased in months with higher anthropogenic disturbance.展开更多
Nodes play different roles or have different functions in many natural and social networks.In this paper,a simple model with different types of nodes and deterministic selective linking rule is proposed.The structural...Nodes play different roles or have different functions in many natural and social networks.In this paper,a simple model with different types of nodes and deterministic selective linking rule is proposed.The structural properties by theoretical predictions are investigated that the given model exhibits a power-law distribution.展开更多
Community structure is an important characteristic in real complex network.It is a network consists ofgroups of nodes within which links are dense but among which links are sparse.In this paper, the evolving network i...Community structure is an important characteristic in real complex network.It is a network consists ofgroups of nodes within which links are dense but among which links are sparse.In this paper, the evolving network includenode, link and community growth and we apply the community size preferential attachment and strength preferentialattachment to a growing weighted network model and utilize weight assigning mechanism from BBV model.Theresulting network reflects the intrinsic community structure with generalized power-law distributions of nodes'degreesand strengths.展开更多
We introduce the generalized rumor spreading model and investigate some properties of this model on different complex social networks. Despite pervious rumor models that both the spreader-spreader (SS) and the spreade...We introduce the generalized rumor spreading model and investigate some properties of this model on different complex social networks. Despite pervious rumor models that both the spreader-spreader (SS) and the spreader-stifler (SR) interactions have the same rate α, we define α(1) and α(2) for SS and SR interactions, respectively. The effect of variation of α(1) and α(2) on the final density of stiflers is investigated. Furthermore, the influence of the topological structure of the network in rumor spreading is studied by analyzing the behavior of several global parameters such as reliability and efficiency. Our results show that while networks with homogeneous connectivity patterns reach a higher reliability, scale-free topologies need a less time to reach a steady state with respect the rumor.展开更多
Stanley Milgram's small world experiment presents "six degrees of separation" of our world.One phenomenon of the experiment still puzzling us is that how individuals operating with the social network inf...Stanley Milgram's small world experiment presents "six degrees of separation" of our world.One phenomenon of the experiment still puzzling us is that how individuals operating with the social network information with their characteristics can be very adept at finding the short chains. The previous works on this issue focus whether on the methods of navigation in a given network structure,or on the effects of additional information to the searching process. In this paper, the authors emphasize that the growth and shape of network architecture is tightly related to the individuals' attributes. The authors introduce a method to reconstruct nodes' intimacy degree based on local interaction. Then we provide an intimacy based approach for orientation in networks. The authors find that the basic reason of efficient search in social networks is that the degree of "intimacy" of each pair of nodes decays with the length of their shortest path exponentially. Meanwhile, the model can explain the hubs limitation which was observed in real-world experiment.展开更多
Most previous studies have mainly focused on the analyses of one entire network(graph) or the giant connected components of networks. In this paper, we investigate the disconnected components(non-giant connected compo...Most previous studies have mainly focused on the analyses of one entire network(graph) or the giant connected components of networks. In this paper, we investigate the disconnected components(non-giant connected component) of some real social networks, and report some interesting discoveries about structural properties of disconnected components. We study three diverse, real networks and compute the significance profile of each component. We discover some similarities in the local structure between the giant connected component and disconnected components in diverse social networks. Then we discuss how to detect network attacks based on the local structure properties of networks. Furthermore, we propose an empirical generative model called i Friends to generate networks that follow our observed patterns.展开更多
The underlying kin structure of groups of animals may be glimpsed from patterns of spatial position or temporal as- sociation between individuals, and is presumed to facilitate inclusive fitness benefits. Such structu...The underlying kin structure of groups of animals may be glimpsed from patterns of spatial position or temporal as- sociation between individuals, and is presumed to facilitate inclusive fitness benefits. Such structure may be evident at a finer, behavioural, scale with individuals preferentially interacting with kin. We tested whether kin structure within groups of meerkats Suricata suricatta matched three forms of social interaction networks： grooming, dominance or foraging competitions. Networks of dominance interactions were positively related to networks of kinship, with close relatives engaging in dominance interactions with each other. This relationship persisted even after excluding the breeding dominant pair and when we restricted the kinship network to only include links between first order kin, which are most likely to be able to discern kin through simple rules of thumb. Conversely, we found no relationship between kinship networks and either grooming networks or networks of foraging competitions. This is surprising because a positive association between kin in a grooming network, or a negative association be- tween kin in a network of foraging competitions offers opportunities for inclusive fitness benefits. Indeed, the positive association between kin in a network of dominance interactions that we did detect does not offer clear inclusive fitness benefits to group members. We conclude that kin structure in behavioural interactions in meerkats may be driven by factors other than indirect fit- ness benefits, and that networks of cooperative behaviours such as grooming may be driven by direct benefits accruing to indi- viduals perhaps through mutualism or manipulation展开更多
Ecological regime shift is the rapid transition from one stable community structure to another, often ecologically infe- rior, stable community. Such regime shifts are especially common in shallow marine communities, ...Ecological regime shift is the rapid transition from one stable community structure to another, often ecologically infe- rior, stable community. Such regime shifts are especially common in shallow marine communities, such as the transition of kelp forests to algal turfs that harbour far lower biodiversity. Stable regimes in communities are a result of balanced interactions be- tween species, and predicting new regimes therefore requires an evaluation of new species interactions, as well as the resilience of the ＇stable＇ position. While computational optimisation techniques can predict new potential regimes, predicting the most likely community state of the various options produced is currently educated guess work. In this study we integrate a stable regime op- timisation approach with a Bayesian network used to infer prior knowledge of the likely stress of climate change （or, in practice, any other disturbance） on each component species of a representative rocky shore community model. Combining the results, by calculating the product of the match between resilient computational predictions and the posterior probabilities of the Bayesian network, gives a refined set of model predictors, and demonstrates the use of the process in determining community changes, as might occur through processes such as climate change. To inform Bayesian priors, we conduct a review of molecular approaches applied to the analysis of the transcriptome of rocky shore organisms, and show how such an approach could be linked to meas- ureable stress variables in the field. Hence species-specific microarrays could be designed as biomarkers of in situ stress, and used to inform predictive modelling approaches such as those described here.展开更多
基金supported by the Yunnan Provincial Science and Technology Infrastructure Program (2011FB105)the National Natural Science Foundation of China (31070349)
文摘We investigated the structure and seasonality of the proximity network in a group of polygynous western black crested gibbons (Nomascus concolor) using social network analysis. The spatial proximity changed seasonally and was affected by temperature and rainfall. Preferred proximity association was not distributed randomly among individuals. Kinship was one explanation for the social structure, as offspring preferred to maintain close proximity with their mothers. The proximity of infants to mothers decreased with age, and independent offspring had lower proximity to mothers than dependent ones. We found that the adult male had different proximity relationships with two different adult females. The frequency of proximity between the male and the infant-carrying female was significantly higher than that between the male and the female who had immigrated carrying one offspring of uncertain paternity into the group. Infanticide avoidance and/or predation protection for dependent infants might explain the proximity relationship differences. Temperature influenced group proximity association, with individual proximity increasing in the cold months and decreasing in the hot months. Group proximity decreased in months with higher anthropogenic disturbance.
文摘Nodes play different roles or have different functions in many natural and social networks.In this paper,a simple model with different types of nodes and deterministic selective linking rule is proposed.The structural properties by theoretical predictions are investigated that the given model exhibits a power-law distribution.
基金Supported by the National Nature Science Foundation of China under Grant No.10832006PuJiang Project of Shanghai under Grant No.09PJ1405000+1 种基金Key Disciplines of Shanghai Municipality (S30104)Research Grant of Shanghai University under Grant No.SHUCX092014
文摘Community structure is an important characteristic in real complex network.It is a network consists ofgroups of nodes within which links are dense but among which links are sparse.In this paper, the evolving network includenode, link and community growth and we apply the community size preferential attachment and strength preferentialattachment to a growing weighted network model and utilize weight assigning mechanism from BBV model.Theresulting network reflects the intrinsic community structure with generalized power-law distributions of nodes'degreesand strengths.
文摘We introduce the generalized rumor spreading model and investigate some properties of this model on different complex social networks. Despite pervious rumor models that both the spreader-spreader (SS) and the spreader-stifler (SR) interactions have the same rate α, we define α(1) and α(2) for SS and SR interactions, respectively. The effect of variation of α(1) and α(2) on the final density of stiflers is investigated. Furthermore, the influence of the topological structure of the network in rumor spreading is studied by analyzing the behavior of several global parameters such as reliability and efficiency. Our results show that while networks with homogeneous connectivity patterns reach a higher reliability, scale-free topologies need a less time to reach a steady state with respect the rumor.
基金supported by the National Natural Science Foundation of China under Grant Nos.61203156,61374175,and 61573065
文摘Stanley Milgram's small world experiment presents "six degrees of separation" of our world.One phenomenon of the experiment still puzzling us is that how individuals operating with the social network information with their characteristics can be very adept at finding the short chains. The previous works on this issue focus whether on the methods of navigation in a given network structure,or on the effects of additional information to the searching process. In this paper, the authors emphasize that the growth and shape of network architecture is tightly related to the individuals' attributes. The authors introduce a method to reconstruct nodes' intimacy degree based on local interaction. Then we provide an intimacy based approach for orientation in networks. The authors find that the basic reason of efficient search in social networks is that the degree of "intimacy" of each pair of nodes decays with the length of their shortest path exponentially. Meanwhile, the model can explain the hubs limitation which was observed in real-world experiment.
基金supported by the National Natural Science Foundation of China (Grant Nos. 61572060, 61190125, 61472024)CERNET Innovation Project 2015 (Grant No. NGII20151004)
文摘Most previous studies have mainly focused on the analyses of one entire network(graph) or the giant connected components of networks. In this paper, we investigate the disconnected components(non-giant connected component) of some real social networks, and report some interesting discoveries about structural properties of disconnected components. We study three diverse, real networks and compute the significance profile of each component. We discover some similarities in the local structure between the giant connected component and disconnected components in diverse social networks. Then we discuss how to detect network attacks based on the local structure properties of networks. Furthermore, we propose an empirical generative model called i Friends to generate networks that follow our observed patterns.
文摘The underlying kin structure of groups of animals may be glimpsed from patterns of spatial position or temporal as- sociation between individuals, and is presumed to facilitate inclusive fitness benefits. Such structure may be evident at a finer, behavioural, scale with individuals preferentially interacting with kin. We tested whether kin structure within groups of meerkats Suricata suricatta matched three forms of social interaction networks： grooming, dominance or foraging competitions. Networks of dominance interactions were positively related to networks of kinship, with close relatives engaging in dominance interactions with each other. This relationship persisted even after excluding the breeding dominant pair and when we restricted the kinship network to only include links between first order kin, which are most likely to be able to discern kin through simple rules of thumb. Conversely, we found no relationship between kinship networks and either grooming networks or networks of foraging competitions. This is surprising because a positive association between kin in a grooming network, or a negative association be- tween kin in a network of foraging competitions offers opportunities for inclusive fitness benefits. Indeed, the positive association between kin in a network of dominance interactions that we did detect does not offer clear inclusive fitness benefits to group members. We conclude that kin structure in behavioural interactions in meerkats may be driven by factors other than indirect fit- ness benefits, and that networks of cooperative behaviours such as grooming may be driven by direct benefits accruing to indi- viduals perhaps through mutualism or manipulation
文摘Ecological regime shift is the rapid transition from one stable community structure to another, often ecologically infe- rior, stable community. Such regime shifts are especially common in shallow marine communities, such as the transition of kelp forests to algal turfs that harbour far lower biodiversity. Stable regimes in communities are a result of balanced interactions be- tween species, and predicting new regimes therefore requires an evaluation of new species interactions, as well as the resilience of the ＇stable＇ position. While computational optimisation techniques can predict new potential regimes, predicting the most likely community state of the various options produced is currently educated guess work. In this study we integrate a stable regime op- timisation approach with a Bayesian network used to infer prior knowledge of the likely stress of climate change （or, in practice, any other disturbance） on each component species of a representative rocky shore community model. Combining the results, by calculating the product of the match between resilient computational predictions and the posterior probabilities of the Bayesian network, gives a refined set of model predictors, and demonstrates the use of the process in determining community changes, as might occur through processes such as climate change. To inform Bayesian priors, we conduct a review of molecular approaches applied to the analysis of the transcriptome of rocky shore organisms, and show how such an approach could be linked to meas- ureable stress variables in the field. Hence species-specific microarrays could be designed as biomarkers of in situ stress, and used to inform predictive modelling approaches such as those described here.
