The Experts below are selected from a list of 52104 Experts worldwide ranked by ideXlab platform
Fernando Vega-redondo - One of the best experts on this subject based on the ideXlab platform.
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Spreading of social Contagions without key players
World Wide Web, 2017Co-Authors: Gizem Korkmaz, Chris J. Kuhlman, S. S. Ravi, Fernando Vega-redondoAbstract:Contagion models have been used to study the spread of social behavior among agents of a networked population. Examples include information diffusion, social influence, and participation in collective action (e.g., protests). Key players, which are typically agents characterized by structural properties of the underlying network (e.g., high degree, high core number or high centrality) are considered important for spreading social Contagions. In this paper, we ask whether Contagions can propagate through a population that is devoid of key players. We justify the use of Erdős-Renyi random graphs as a representation of unstructured populations that lack key players, and investigate whether complex Contagions—those requiring reinforcement—can spread on them. We demonstrate that two game-theoretic Contagion models that utilize common knowledge for collective action can readily spread such Contagions, thus differing significantly from classic complex Contagion models. We compare Contagion dynamics results on unstructured networks to those on more typically-studied, structured social networks to understand the role of network structure. We test the classic complex Contagion and the two game-theoretic models with a total of 18 networks that range over five orders of magnitude in size and have different structural properties. The two common knowledge models are also contrasted to understand the effects of different modeling assumptions on dynamics. We show that under a wide range of conditions, these two models produce markedly different results. Finally, we demonstrate that the disparity between classic complex Contagion and common knowledge models persists as network size increases.
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BESC - Can social Contagion spread without key players
2016 International Conference on Behavioral Economic and Socio-cultural Computing (BESC), 2016Co-Authors: Gizem Korkmaz, Chris J. Kuhlman, Fernando Vega-redondoAbstract:Contagion models have been used to study the spread of social behavior among agents of a population, such as information diffusion, social influence, and participation to collective action (e.g., protests). Key players, which are typically high-degree, -k-core or -centrality agents in a networked population, are considered important for spreading social Contagions. In this paper, we ask whether Contagions can propagate through a population that is void of key players. We use Erdos-Renyi random graphs as a representation of unstructured populations that lack key players, and investigate whether complex Contagions — those requiring reinforcement — can spread on them. We demonstrate that two game-theoretic Contagion models that utilize common knowledge for collective action can readily spread such Contagions, which is a significant difference from classic complex Contagion models. We compare Contagion dynamics results on unstructured networks to those on more typically-studied, structured social networks to understand the role of network structure. We test a total of 14 networks. The two common knowledge models are also contrasted to understand the effects of different modeling assumptions on dynamics. We show that under a wide range of conditions, these two models produce markedly different results.
Chris J. Kuhlman - One of the best experts on this subject based on the ideXlab platform.
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Spreading of social Contagions without key players
World Wide Web, 2017Co-Authors: Gizem Korkmaz, Chris J. Kuhlman, S. S. Ravi, Fernando Vega-redondoAbstract:Contagion models have been used to study the spread of social behavior among agents of a networked population. Examples include information diffusion, social influence, and participation in collective action (e.g., protests). Key players, which are typically agents characterized by structural properties of the underlying network (e.g., high degree, high core number or high centrality) are considered important for spreading social Contagions. In this paper, we ask whether Contagions can propagate through a population that is devoid of key players. We justify the use of Erdős-Renyi random graphs as a representation of unstructured populations that lack key players, and investigate whether complex Contagions—those requiring reinforcement—can spread on them. We demonstrate that two game-theoretic Contagion models that utilize common knowledge for collective action can readily spread such Contagions, thus differing significantly from classic complex Contagion models. We compare Contagion dynamics results on unstructured networks to those on more typically-studied, structured social networks to understand the role of network structure. We test the classic complex Contagion and the two game-theoretic models with a total of 18 networks that range over five orders of magnitude in size and have different structural properties. The two common knowledge models are also contrasted to understand the effects of different modeling assumptions on dynamics. We show that under a wide range of conditions, these two models produce markedly different results. Finally, we demonstrate that the disparity between classic complex Contagion and common knowledge models persists as network size increases.
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BESC - Can social Contagion spread without key players
2016 International Conference on Behavioral Economic and Socio-cultural Computing (BESC), 2016Co-Authors: Gizem Korkmaz, Chris J. Kuhlman, Fernando Vega-redondoAbstract:Contagion models have been used to study the spread of social behavior among agents of a population, such as information diffusion, social influence, and participation to collective action (e.g., protests). Key players, which are typically high-degree, -k-core or -centrality agents in a networked population, are considered important for spreading social Contagions. In this paper, we ask whether Contagions can propagate through a population that is void of key players. We use Erdos-Renyi random graphs as a representation of unstructured populations that lack key players, and investigate whether complex Contagions — those requiring reinforcement — can spread on them. We demonstrate that two game-theoretic Contagion models that utilize common knowledge for collective action can readily spread such Contagions, which is a significant difference from classic complex Contagion models. We compare Contagion dynamics results on unstructured networks to those on more typically-studied, structured social networks to understand the role of network structure. We test a total of 14 networks. The two common knowledge models are also contrasted to understand the effects of different modeling assumptions on dynamics. We show that under a wide range of conditions, these two models produce markedly different results.
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Inhibiting diffusion of complex Contagions in social networks: theoretical and experimental results
Data Mining and Knowledge Discovery, 2015Co-Authors: Chris J. Kuhlman, S. S. Ravi, V. S. Anil Kumar, Madhav V. Marathe, Daniel J. RosenkrantzAbstract:We consider the problem of inhibiting undesirable Contagions (e.g. rumors, spread of mob behavior) in social networks. Much of the work in this context has been carried out under the 1-threshold model, where diffusion occurs when a node has just one neighbor with the Contagion. We study the problem of inhibiting more complex Contagions in social networks where nodes may have thresholds larger than 1. The goal is to minimize the propagation of the Contagion by removing a small number of nodes (called critical nodes ) from the network. We study several versions of this problem and prove that, in general, they cannot even be efficiently approximated to within any factor $$\rho \ge 1$$ ρ ≥ 1 , unless P = NP . We develop efficient and practical heuristics for these problems and carry out an experimental study of their performance on three well known social networks, namely epinions , wikipedia and slashdot . Our results show that these heuristics perform significantly better than five other known methods. We also establish an efficiently computable upper bound on the number of nodes to which a Contagion can spread and evaluate this bound on many real and synthetic networks.
Lidia A Braunstein - One of the best experts on this subject based on the ideXlab platform.
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modeling risk Contagion in the venture capital market a multilayer network approach
Complexity, 2019Co-Authors: L D Valdez, Lidia A Braunstein, H. E. Stanley, Xin ZhangAbstract:Venture capital plays a critical role in spurring innovation, encouraging entrepreneurship, and generating wealth. As a part of the financial market, venture capital is affected by market downturns and economic cycles, but it also creates bubbles that negatively impact the economy and social stability. Although the venture capital market is a potential source of systemic risk, there has been little study of its Contagion risk mechanism, or how the failure of a single market participant can threaten systemic stability. We use a multilayer network analysis to model the risk Contagion in a venture capital market when an external shock impacts a venture capital firm or start-up company in order to understand how risk can spread through connections between market participants and harm total market robustness. We use our model to describe both the direct and indirect channels in the venture capital market that propagates risk and loss. Using real data from the worldwide venture capital market, we find that the venture capital market exhibits the same “robust-yet-fragile” feature as other financial systems. The coupling effect of direct and indirect risk Contagions can cause abrupt transitions and large-scale damage even when the turbulence is minor. We also find that the network structure, connectivity, and cash position distribution of market participants impact market robustness. Our study complements other emerging research on measuring systemic risk through multiple connections among market players and on the feedback risk Contagion between the financial industry and the real economy.
Stuart Parsons - One of the best experts on this subject based on the ideXlab platform.
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Positive emotional Contagion in a New Zealand parrot
Current Biology, 2017Co-Authors: Raoul Schwing, Ximena J. Nelson, Amelia Wein, Stuart ParsonsAbstract:Positive emotional Contagions are outwardly emotive actions that spread from one individual to another, such as glee in preschool children [1] or laughter in humans of all ages [2]. The play vocalizations of some animals may also act as emotional Contagions. For example, artificially deafened rats are less likely to play than their non-hearing-impaired conspecifics, while no such effect is found for blinded rats [3]. As rat play vocalizations are also produced in anticipation of play, they, rather than the play itself, may act as a Contagion, leading to a hypothesis of evolutionary parallels between rat play vocalizations and human laughter [4]. The kea parrot (Nestor notabilis) has complex play behaviour and a distinct play vocalization [5]. We used acoustic playback to investigate the effect of play calls on wild kea, finding that play vocalizations increase the amount of play among both juveniles and adults, likely by acting as a positive emotional Contagion.
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Positive emotional Contagion in a New Zealand parrot [Correspondence]
Current Biology, 2017Co-Authors: Raoul Schwing, Ximena J. Nelson, Amelia Wein, Stuart ParsonsAbstract:Summary Positive emotional Contagions are outwardly emotive actions that spread from one individual to another, such as glee in preschool children [1] or laughter in humans of all ages [2]. The play vocalizations of some animals may also act as emotional Contagions. For example, artificially deafened rats are less likely to play than their non-hearing-impaired conspecifics, while no such effect is found for blinded rats [3]. As rat play vocalizations are also produced in anticipation of play, they, rather than the play itself, may act as a Contagion, leading to a hypothesis of evolutionary parallels between rat play vocalizations and human laughter [4]. The kea parrot (Nestor notabilis) has complex play behaviour and a distinct play vocalization [5]. We used acoustic playback to investigate the effect of play calls on wild kea, finding that play vocalizations increase the amount of play among both juveniles and adults, likely by acting as a positive emotional Contagion.
Gizem Korkmaz - One of the best experts on this subject based on the ideXlab platform.
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Spreading of social Contagions without key players
World Wide Web, 2017Co-Authors: Gizem Korkmaz, Chris J. Kuhlman, S. S. Ravi, Fernando Vega-redondoAbstract:Contagion models have been used to study the spread of social behavior among agents of a networked population. Examples include information diffusion, social influence, and participation in collective action (e.g., protests). Key players, which are typically agents characterized by structural properties of the underlying network (e.g., high degree, high core number or high centrality) are considered important for spreading social Contagions. In this paper, we ask whether Contagions can propagate through a population that is devoid of key players. We justify the use of Erdős-Renyi random graphs as a representation of unstructured populations that lack key players, and investigate whether complex Contagions—those requiring reinforcement—can spread on them. We demonstrate that two game-theoretic Contagion models that utilize common knowledge for collective action can readily spread such Contagions, thus differing significantly from classic complex Contagion models. We compare Contagion dynamics results on unstructured networks to those on more typically-studied, structured social networks to understand the role of network structure. We test the classic complex Contagion and the two game-theoretic models with a total of 18 networks that range over five orders of magnitude in size and have different structural properties. The two common knowledge models are also contrasted to understand the effects of different modeling assumptions on dynamics. We show that under a wide range of conditions, these two models produce markedly different results. Finally, we demonstrate that the disparity between classic complex Contagion and common knowledge models persists as network size increases.
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BESC - Can social Contagion spread without key players
2016 International Conference on Behavioral Economic and Socio-cultural Computing (BESC), 2016Co-Authors: Gizem Korkmaz, Chris J. Kuhlman, Fernando Vega-redondoAbstract:Contagion models have been used to study the spread of social behavior among agents of a population, such as information diffusion, social influence, and participation to collective action (e.g., protests). Key players, which are typically high-degree, -k-core or -centrality agents in a networked population, are considered important for spreading social Contagions. In this paper, we ask whether Contagions can propagate through a population that is void of key players. We use Erdos-Renyi random graphs as a representation of unstructured populations that lack key players, and investigate whether complex Contagions — those requiring reinforcement — can spread on them. We demonstrate that two game-theoretic Contagion models that utilize common knowledge for collective action can readily spread such Contagions, which is a significant difference from classic complex Contagion models. We compare Contagion dynamics results on unstructured networks to those on more typically-studied, structured social networks to understand the role of network structure. We test a total of 14 networks. The two common knowledge models are also contrasted to understand the effects of different modeling assumptions on dynamics. We show that under a wide range of conditions, these two models produce markedly different results.
