Ligação Preferencial e Aptidão na Evolução da Rede de Filmes Brasileiros

Abstract This study analyzes the network evolution, specifically that of the Brazilian film network. It examines two generative mechanisms that lie behind the network evolution: preferential attachment and fitness. The starting point is that preferential attachment and fitness may compete to shape the network evolution. We built a novel dataset with 974 Brazilian feature films released between 1995 and 2017 and used PAFit, a brand-new statistical method, to estimate the joint effects of preferential attachment and fitness on the evolution of the Brazilian film network. This study concludes that the network evolution is shaped by both preferential attachment and fitness. However, in the presence of fitness, the effects of preferential attachment on the network evolution become weaker. This means that the node ability to form ties in the Brazilian film network is mainly explained by its fitness. Besides, the preferential attachment assumes a sub-linear form. Costs, communication and managerial capabilities, and node age explain why nodes are unable to accumulate ties at rates proportional to their degree. Finally, preferential attachment and fitness manifest themselves heterogeneously, depending on either the type or the duration of the network. Preferential attachment drives the cast network evolution, whereas fitness is the main generative mechanism of the crew network. Actors and actresses rely on their status, privilege, and power to obtain future contracts (preferential attachment), whereas technical members are selected on the basis of their talent, skills, and knowledge (fitness). Due to node age or exit, preferential attachment becomes stronger in shorter networks.

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Estimating Local Decision-Making Behavior in Complex Evolutionary Systems

Journal of Mechanical Design ◽

10.1115/1.4026823 ◽

2014 ◽

Vol 136 (6) ◽

Cited By ~ 7

Author(s):

Zhenghui Sha ◽

Jitesh H. Panchal

Keyword(s):

Decision Making ◽

Systems Engineering ◽

Choice Model ◽

Preferential Attachment ◽

Network Evolution ◽

System Structure ◽

Statistical Regression ◽

Evolutionary Systems ◽

Local Decision ◽

Local Decision Making

Research in systems engineering and design is increasingly focused on complex sociotechnical systems whose structures are not directly controlled by the designers, but evolve endogenously as a result of decisions and behaviors of self-directed entities. Examples of such systems include smart electric grids, Internet, smart transportation networks, and open source product development communities. To influence the structure and performance of such systems, it is crucial to understand the local decisions that result in observed system structures. This paper presents three approaches to estimate the local behaviors and preferences in complex evolutionary systems, modeled as networks, from its structure at different time steps. The first approach is based on the generalized preferential attachment model of network evolution. In the second approach, statistical regression-based models are used to estimate the local decision-making behaviors from consecutive snapshots of the system structure. In the third approach, the entities are modeled as rational decision-making agents who make linking decisions based on the maximization of their payoffs. Within the decision-centric framework, the multinomial logit choice model is adopted to estimate the preferences of decision-making nodes. The approaches are illustrated and compared using an example of the autonomous system (AS) level Internet. The approaches are generally applicable to a variety of complex systems that can be modeled as networks. The insights gained are expected to direct researchers in choosing the most applicable estimation approach to get the node-level behaviors in the context of different scenarios.

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Rethinking Proxy War Theory in IR: A Critical Analysis of Principal–Agent Theory

International Studies Review ◽

10.1093/isr/viab050 ◽

2021 ◽

Author(s):

Abbas Farasoo

Keyword(s):

Critical Analysis ◽

Principal Agent ◽

Principal Agent Theory ◽

Agent Theory ◽

Proxy War ◽

Generative Mechanism ◽

Generative Mechanisms ◽

Different Levels ◽

Domestic Level

Abstract This paper explores the question of what drives proxy alignment in war and argues that current proxy war scholarship needs further thinking to go beyond focusing on the principal–agent theory and individual actors’ motivation analysis. Rather, there is a need to look at the generative mechanisms of proxy alignment as a process that constitutes patterns of friend–enemy relations. The paper argues securitization patterns from domestic to regional and international levels drive actors to re-evaluate their positions and define their enemies and friends. This is a process of securitization alignment and confluence, which serves as a generative mechanism for proxy alignment in a conflict. Securitization alignment is based on a convergence of securitizations by different actors that create a friend–enemy dynamic and convergence of security interests between actors. The confluence of securitizations from the domestic level to regional and beyond also connects actors across different levels to be in alignment and impact the conflict.

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A stochastic generative model of the World Trade Network

Scientific Reports ◽

10.1038/s41598-019-54979-1 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 1

Author(s):

Javier García-Algarra ◽

Mary Luz Mouronte-López ◽

Javier Galeano

Keyword(s):

Stochastic Model ◽

World Trade ◽

Preferential Attachment ◽

Weighted Degree ◽

Trade Network ◽

Exchange Flows ◽

The World ◽

Generative Mechanisms ◽

Source Of Information ◽

Synthetic Networks

AbstractThe World Trade Network (WTN) is a network of exchange flows among countries whose topological and statistical properties are a valuable source of information. Degree and strength (weighted degree) are key magnitudes to understand its structure and generative mechanisms. In this work, we describe a stochastic model that yields synthetic networks that closely mimic the properties of annual empirical data. The model combines two popular mechanisms of network generation: preferential attachment and multiplicative process. Agreement between empirical and synthetic networks is checked using the available series from 1962 to 2017.

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A Novel Wireless Sensor Network Evolution Model Based on Energy-Efficiency

International Journal of Online Engineering (iJOE) ◽

10.3991/ijoe.v13i03.6855 ◽

2017 ◽

Vol 13 (03) ◽

pp. 4 ◽

Cited By ~ 1

Author(s):

Hui Gao ◽

Zhixian Yang

Keyword(s):

Preferential Attachment ◽

Influence Factors ◽

Network Evolution ◽

Evolution Model ◽

Wireless Sensor ◽

Font Size ◽

Total Energy Consumption ◽

Scale Free ◽

Random Node ◽

Attachment Mechanism

<span style="font-family: 'Times New Roman',serif; font-size: 12pt; mso-fareast-font-family: SimSun; mso-fareast-theme-font: minor-fareast; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;">The Barabási–Albert (BA) model is a famous complex network model that generates scale-free networks. Wireless sensor networks (WSNs) had been thought to be approximately scale-free through lots of empirical research. Based on the BA model, we propose an evolution model for WSNs. According to actual influence factors such as the remainder energy of each sensor and physical link capability of each sensor, our evolution model constructs WSNs by using a preferential attachment mechanism. Through simulation and analysis, we can prove that our evolution model would make the total energy consumption of the WSNs more efficient and have a superior random node error tolerance.</span>

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The N-star network evolution model

Journal of Applied Probability ◽

10.1017/jpr.2019.21 ◽

2019 ◽

Vol 56 (2) ◽

pp. 416-440 ◽

Cited By ~ 1

Author(s):

István Fazekas ◽

Csaba Noszály ◽

Attila Perecsényi

Keyword(s):

Power Law ◽

Preferential Attachment ◽

Network Evolution ◽

Evolution Model ◽

Asymptotic Power ◽

Star Network ◽

Power Law Distributions

AbstractA new network evolution model is introduced in this paper. The model is based on cooperations of N units. The units are the nodes of the network and the cooperations are indicated by directed links. At each evolution step N units cooperate, which formally means that they form a directed N-star subgraph. At each step either a new unit joins the network and it cooperates with N − 1 old units, or N old units cooperate. During the evolution both preferential attachment and uniform choice are applied. Asymptotic power law distributions are obtained both for in-degrees and for out-degrees.

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Epidemic spreading on evolving networks

International Journal of Modern Physics B ◽

10.1142/s0217979219502667 ◽

2019 ◽

Vol 33 (23) ◽

pp. 1950266 ◽

Cited By ~ 2

Author(s):

Jin-Xuan Yang

Keyword(s):

Preferential Attachment ◽

Small World ◽

Network Evolution ◽

Epidemic Spreading ◽

Epidemic Threshold ◽

Scale Free ◽

Evolving Networks ◽

Power Law Exponent ◽

Free Network ◽

Over Time

Network structure will evolve over time, which will lead to changes in the spread of the epidemic. In this work, a network evolution model based on the principle of preferential attachment is proposed. The network will evolve into a scale-free network with a power-law exponent between 2 and 3 by our model, where the exponent is determined by the evolution parameters. We analyze the epidemic spreading process as the network evolves from a small-world one to a scale-free one, including the changes in epidemic threshold over time. The condition of epidemic threshold to increase is given with the evolution processes. The simulated results of real-world networks and synthetic networks show that as the network evolves at a low evolution rate, it is more conducive to preventing epidemic spreading.

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A WEIGHTED NETWORK EVOLUTION WITH TRAFFIC FLOW UNDER PREFERENTIAL ATTACHMENT

International Journal of Modern Physics C ◽

10.1142/s0129183113500204 ◽

2013 ◽

Vol 24 (04) ◽

pp. 1350020 ◽

Cited By ~ 3

Author(s):

MEIFENG DAI ◽

RONGRONG LU

Keyword(s):

Traffic Flow ◽

Network Model ◽

Traditional Method ◽

Preferential Attachment ◽

Transportation System ◽

Network Evolution ◽

Random Component ◽

Weighted Network ◽

Scale Free ◽

Weighted Networks

With more attentions drawn to transportation, we find that it is available to analyze transportation system by using weighted networks. Distinguishing from traditional method, we introduce a dynamic weighted network model with evolutional size and weight. Additionally, the expected strength allocation vector of the model consists of a deterministic component reflecting preferential attachment and a random component, which can characterize the realistic network better. In this paper, we obtain the degree and strength distributions of the weighted network and we conclude that the network has scale-free characteristics.

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Skirts in the lab: Madame Curie and the image of the woman scientist in the feature film

Public Understanding of Science ◽

10.1088/0963-6625/6/3/005 ◽

1997 ◽

Vol 6 (3) ◽

pp. 269-278 ◽

Cited By ~ 11

Author(s):

Alberto Elena

Keyword(s):

Significant Role ◽

Women Scientists ◽

Woman Scientist ◽

Feature Film ◽

Distinctive Features ◽

Feature Films ◽

Starting Point ◽

The Subject ◽

The Creation

Recent research has appropriately emphasized the significant role played by feature films in the creation (as well as the reflection) of popular stereotypes of the scientist. However, no particular study has yet been devoted to the depiction of women scientists in the cinema, even though it is quite clear that this presents its own distinctive features. Taking the influential Madame Curie (Mervyn LeRoy, 1943) as a starting point, this paper attempts to give a first overview of the subject.

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K-clique percolation in free association networks. The mechanism behind the 7 ± 2 law?

10.21203/rs.3.rs-1031550/v1 ◽

2021 ◽

Author(s):

Olga Valba ◽

Alexander Gorsky

Keyword(s):

Community Organization ◽

Preferential Attachment ◽

Free Association ◽

Small World ◽

Semantic Networks ◽

Network Evolution ◽

Cognitive Networks ◽

Qualitative Explanation ◽

Capacity Limit ◽

Clique Percolation

Abstract It is important to reveal the mechanisms of propagation in different cognitive networks. In this study we discuss the k-clique percolation phenomenon on the free association networks including "English Small World of Words project" (SWOW-EN). We compare different semantic networks and networks of free associations for different languages. Surprisingly it turned out that k-clique percolation for all k < k c = (6 − 7) is possible on free association networks of different languages. Our analysis suggests the new universality patterns for a community organization of free association networks. We conjecture that our result can provide the qualitative explanation of the Miller’s 7 ± 2 rule for the capacity limit of working memory. The new model of network evolution extending the preferential attachment is suggested which provides the observed value of k c .

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