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Comparing the Survival Analysis of Two or More Groups01:20

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Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
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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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Social Foundations of Self IV: Self in Digital Communication01:30

Social Foundations of Self IV: Self in Digital Communication

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Since the early 2000s, computer-mediated communication (CMC) has grown rapidly, playing a crucial role in self-development. A key distinction between CMC and real-life interactions is the lack of a physically present partner. This absence makes non-verbal cues such as facial expressions, body language, and paralinguistic signals unavailable in CMC platforms like email, instant messaging, or social media. The lack of these cues can create ambiguity and complicate how feedback is interpreted.The...
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Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

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Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
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Impact of Groups on Groups

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Social psychologists analyze how groups influence one another, shaping social structures and interactions through both cooperation and competition. These dynamics manifest in various ways, ranging from economic partnerships to intergroup conflicts that shape societal structures and perceptions.Cooperation and Competition in Intergroup RelationsIntergroup relationships vary across contexts, sometimes fostering cooperation and mutual benefit while at other times leading to conflict and...
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相关实验视频

Updated: Jan 8, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

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使用功能数据分析比较社交媒体社区.

Xiaoxia Champon1, Jasser Jasser2, Chathura Jayalath3

  • 1North Carolina State University.

Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences
|December 22, 2025
PubMed
概括

社交媒体社区的分歧,塑造信息流. 分析时间帖子和转发数据揭示了虚假信息策略和社区差异,这对于理解信息传播至关重要.

科学领域:

  • 社会科学 社会科学 社会科学
  • 计算社会科学 计算社会科学
  • 信息科学 信息科学 信息科学

背景情况:

  • 社交媒体平台托管着不同对话轨迹的多元化社区.
  • 虚假信息和操纵的信息可以显著影响公众论.
  • 了解集团间的差异是分析信息流的关键.

研究的目的:

  • 量化对立社交媒体社区之间的差异.
  • 揭示这些社区用于宣传活动的独特策略.
  • 分析在线小组中信息传播的时间动态.

主要方法:

  • 利用功能数据分析来检查社交媒体群体的时间动态.
  • 通过使用时间依赖的指标 (如帖子和转发) 评估小组行为.
  • 调查了与备受目的事件 (斯克里帕尔/诺维乔克,布查犯罪) 相关的Twitter数据.

主要成果:

  • 初步发现突出了社区之间信息传播策略的可量化的差异.
  • 确定了与特定活动相关的帖子和转发活动的时间模式.
  • 揭示了对抗在线团体使用的独特的行为机制.

结论:

关键词:
社交媒体 社交媒体功能性数据分析数据分析.群体差异是群体之间的差异.

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  • 该研究提供了对社交媒体信息传播机制的新见解.
  • 量化社区差异有助于理解信息和虚假信息的传播.
  • 调查结果可以为在线活动的最佳响应时间制定策略.