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相关概念视频

Social Exchange Theory02:06

Social Exchange Theory

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We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
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Social Exchange Theory01:26

Social Exchange Theory

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As formulated by John Thibaut and Harold Kelley, Social Exchange Theory explains human relationships as economic-like exchanges that maximize rewards and minimize costs. This theory suggests that individuals engage in relationships to gain benefits and reduce burdens, similar to economic transactions. It has been widely applied to various types of relationships, including romantic, professional, and social interactions.Rewards and Costs in RelationshipsRelationship rewards include emotional...
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Relationship Formation02:12

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What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
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Impact of Individuals on Individuals01:30

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Human behavior is intricately shaped by social influences that arise from interactions with others in diverse contexts. These influences not only mold beliefs and attitudes but also drive the regulation of behaviors through both direct communication and observational learning. The study of these processes falls within the domain of social psychology, which seeks to understand how individuals are affected by and affect those around them.Mechanisms of Social InfluenceDirect social influence...
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Causes of Social Behavior I: Actions and Characteristics of Individuals01:30

Causes of Social Behavior I: Actions and Characteristics of Individuals

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The actions and characteristics of others heavily influence the causes of social behaviors. Emotional expressions serve as powerful social signals, shaping behaviors and interactions in significant ways. Whether through direct observation or subconscious processing, individuals constantly adjust their responses based on the emotions and attributes of those around them.Emotional Cues and Social ResponsesFacial expressions, tone of voice, and body language provide crucial emotional cues that...
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Causes of Social Behavior III: Biological and Environmental Influences01:28

Causes of Social Behavior III: Biological and Environmental Influences

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Social behavior is a complex phenomenon that arises from the interaction between biological predispositions and environmental influences. This intricate interplay shapes how individuals think, feel, and act in various social contexts. Understanding these mechanisms requires insights from psychology, neuroscience, genetics, and evolutionary theory.Environmental Influences on Social BehaviorEnvironmental factors, including temperature, odors, and visual stimuli, play a crucial role in shaping...
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相关实验视频

Updated: Jan 15, 2026

Assessment of Social Interaction Behaviors
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Assessment of Social Interaction Behaviors

Published on: February 25, 2011

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在赋予的交互网络上挖掘特殊的社会行为.

Martin Atzmueller1,2,3, Carolina Centeio Jorge4,5, Cláudio Rebelo de Sá4,5

  • 1Osnabrück University, Osnabrück, Germany.

Machine learning
|October 13, 2025
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概括
此摘要是机器生成的。

这项研究引入了一种分析社会互动网络的新方法,重点关注双层结构和属性. 它使用时空数据,相互作用的持续时间和频率来识别具有特殊行为的子组.

关键词:
双性分析 (Dyadic Analysis) 是一种两性分析.社交互动网络是社会互动网络.发现子组的发现.

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Last Updated: Jan 15, 2026

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Brain Imaging Investigation of the Neural Correlates of Observing Virtual Social Interactions

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科学领域:

  • 社交网络分析 社交网络分析
  • 数据挖掘 数据挖掘
  • 计算社会科学 计算社会科学

背景情况:

  • 社交互动越来越多地通过在线和离线传感器记录,形成时间印的互动网络.
  • 分析这些网络通常涉及识别具有独特行为模式的子组,通常专注于网络结构.
  • 归因的社交网络提供了更丰富的数据,包括除了简单的连接之外的额外属性.

研究的目的:

  • 提出一种新的方法来识别社会交互网络中特殊的社会行为模式.
  • 专注于这些网络的双层结构,使其能够进行组成分析.
  • 调整本地模式挖掘和子组发现技术以适应时空归因交互数据.

主要方法:

  • 该方法将时空交互数据模型作为归属的社交网络.
  • 它适应了本地模式挖掘和子组发现,以分析二结构和属性.
  • 提出了七个新的质量函数,用于测量确定子组的有趣性,考虑相互作用的持续时间和频率.

主要成果:

  • 该方法在四个现实数据集上进行了评估,包括学术会议和学校游乐场互动.
  • 这种方法成功地确定了展示特殊社会行为的有趣,有意义和有效的子组.
  • 结果表明,利用双层结构和属性在社交互动网络中发现子组的有效性.

结论:

  • 拟议的方法通过分析时空归因交互网络,有效地识别出具有偏差社会行为的子组.
  • 专注于二次结构和属性为子组发现提供了一个强大的组成视角.
  • 新的质量功能增强了在复杂的社会互动数据中找到重要模式的能力.