Personality Characteristics of Gifted Israeli Children

Milgram, Roberta M.; Milgram, Norman A.

doi:10.1080/00221325.1976.10534029

Cited by 86 publications

(91 citation statements)

References 3 publications

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“…Yet, the small-world property (ii) has been completely neglected. There are different paths to estimate D. First, we can use a direct approach as the Milgram's experiments [32]. Second, we can measure other network properties such as the degree distribution and then try to estimate D using network models [34,35,36,37,38,48].…”

Section: Discussionmentioning

confidence: 99%

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Spreading dynamics on heterogeneous populations: Multitype network approach

Vázquez

2006

Phys. Rev. E

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I study the spreading of infectious diseases on heterogeneous populations. I represent the population structure by a contact-graph where vertices represent agents and edges represent disease transmission channels among them. The population heterogeneity is taken into account by the agent's subdivision in types and the mixing matrix among them. I introduce a type-network representation for the mixing matrix allowing an intuitive understanding of the mixing patterns and the analytical calculations. Using an iterative approach I obtain recursive equations for the probability distribution of the outbreak size as a function of time. I demonstrate that the expected outbreak size and its progression in time are determined by the largest eigenvalue of the reproductive number matrix and the characteristic distance between agents on the contact-graph. Finally, I discuss the impact of intervention strategies to halt epidemic outbreaks. This work provides both a qualitative understanding and tools to obtain quantitative predictions for the spreading dynamics on heterogeneous populations.

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Section: Discussionmentioning

confidence: 99%

“…Social experiments such as the Kevin Bacon and Erdős numbers [31] or the Milgram experiment [32] reveal that social actors are separated by a small number of acquaintances ("small-world" property [33]). This observation is supported by theoretical approaches demonstrating that D grows at most as log N in random graphs [34,35,36,37].…”

Section: A Contact-graphmentioning

confidence: 99%

Spreading dynamics on heterogeneous populations: Multitype network approach

Vázquez

2006

Phys. Rev. E

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“…On the other hand, the clustering coefficient C does not depend on N for a regular lattice, while it goes to zero in large random graphs. From these two limiting cases one could argue that short L is always associated with small C, and long L with large C. Instead social systems, which are a paradigmatic example of a small-world network, can exhibit, at the same time, short characteristic path length [8] like random graphs, and high clustering [26]. Now we can come back to the WS model.…”

Section: The Small-world Behavior: the Ws Modelmentioning

confidence: 99%

“…The characteristic path length L One of the most important quantities to characterize the properties of a graph is the geodesic, or the shortest path length between two vertices (popularly known in social networks as the number of degrees of separation [8,22,23]). The shortest path length d ij between i and j is the minimum number of edges traversed to get from a vertex i to another vertex j.…”

Section: The Ws Formulationmentioning

confidence: 99%

“…In a recent paper Watts and Strogatz have shown that the connection topology of some biological, technological and social networks is neither completely regular nor completely random [6,7], but stays somehow in between these two extreme cases. These particular class of networks, named small worlds in analogy with the concept of small-world phenomenon developed 30 years ago in social psychology [8], are in fact highly clustered like regular lattices, yet having small characteristic path lengths like random graphs. A pictorial description of this situation is that the networks' complexity lies at the edge of order and chaos.…”

Section: Introductionmentioning

confidence: 99%

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Economic small-world behavior in weighted networks

2003

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The small-world phenomenon has been already the subject of a huge variety of papers, showing its appeareance in a variety of systems. However, some big holes still remain to be filled, as the commonly adopted mathematical formulation suffers from a variety of limitations, that make it unsuitable to provide a general tool of analysis for real networks, and not just for mathematical (topological) abstractions. In this paper we show where the major problems arise, and how there is therefore the need for a new reformulation of the small-world concept. Together with an analysis of the variables involved, we then propose a new theory of small-world networks based on two leading concepts: efficiency and cost. Efficiency measures how well information propagates over the network, and cost measures how expensive it is to build a network. The combination of these factors leads us to introduce the concept of economic small worlds, that formalizes the idea of networks that are "cheap" to build, and nevertheless efficient in propagating information, both at global and local scale. This new concept is shown to overcome all the limitations proper of the so-far commonly adopted formulation, and to provide an adequate tool to quantitatively analyze the behaviour of complex networks in the real world. Various complex systems are analyzed, ranging from the realm of neural networks, to social sciences, to communication and transportation networks. In each case, economic small worlds are found. Moreover, using the economic small-world framework, the construction principles of these networks can be quantitatively analyzed and compared, giving good insights on how efficiency and economy principles combine up to shape all these systems.

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Effects of Academic Achievement and Gender on Academic and Social Self‐Concept: A Replication Study

Kelly

Jordan

1990

Jour of Counseling & Develop

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Female and male eighth‐grade students representing very high, moderately high, and average levels of achievement were compared on measures of academic and social self‐concept. Most of the differences were in academic self‐concept, which was positively related to level of academic achievement. There also was an interaction of gender and academic achievement on academic self‐concept. Average achieving girls had lower academic self‐concept scores than all other groups of students. In addition, boys scored higher than girls on measures of academic self‐concept and job competence. There were no significant differences on any of the social self‐concept measures. The counseling implications of these findings for gifted students and girls of average achievement are discussed.

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Personality Characteristics of Gifted Israeli Children

Cited by 86 publications

References 3 publications

Spreading dynamics on heterogeneous populations: Multitype network approach

Spreading dynamics on heterogeneous populations: Multitype network approach

Economic small-world behavior in weighted networks

Effects of Academic Achievement and Gender on Academic and Social Self‐Concept: A Replication Study

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