适当的网络随机化是评估社会平衡的关键
Bingjie Hao1, István A Kovács1,2,3
1Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208, USA.
Science advances
|May 3, 2024
概括
当前的零模型无法检测签名网络中的强平衡. 新的STP零模型,保留网络拓和节点程度偏好,准确地识别了社交网络中的平衡.
科学领域:
- 社交网络分析分析
- 图形理论是指图形的理论.
- 统计建模 统计建模
背景情况:
- 积极或消极的社会关系,形成由平衡理论分析的签名网络模式.
- 评估这些模式的统计学意义通常涉及零模型,但在签名网络的结果往往是有争议的.
- 现有的零模型可能无法识别强平衡,即使在构建以展示强平衡的网络中也是如此.
研究的目的:
- 在签名网络分析中解决当前零模型的争议和局限性.
- 引入一个新的零模型,准确地识别社交网络中的平衡模式.
- 探索改善平衡检测对理解社交网络结构的影响.
主要方法:
- 开发和应用的签名拓保护 (STP) 零模型.
- 在最大框架内集成节点签名度偏好和网络拓保存.
- 将STP随机化结果与社交网络的传统零模型进行比较.
主要成果:
- STP零模型揭示了许多社交网络在三节点和四节点模式中表现出强大的平衡,这些模式以前未被检测到.
- 保持签名度偏好和网络拓对于准确的平衡评估至关重要.
- 与现有的零模型相比,STP随机化产生了质量上不同的和更一致的结果.
结论:
- 拟议的STP零模型为评估签名社交网络中的平衡提供了更可靠的方法.
- 这些发现表明,潜在的布线机制驱动社会互动中观察到的签名模式.
- 该STP框架具有广泛的适用性,用于签名网络分析的未来研究.
相关概念视频
Randomized Experiments
6.9K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
6.9K
Group Design
8.9K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
8.9K
Wald-Wolfowitz Runs Test I
642
The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
The test works...
642
Wald-Wolfowitz Runs Test II
232
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
232
Random Sampling Method
11.1K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
11.1K
Random Variables
11.7K
A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
11.7K


