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相关概念视频

Group Polarization01:01

Group Polarization

34.3K
Group polarization is the strengthening of an original group attitude following the discussion of views within a group (Teger & Pruitt, 1967). That is, if a group initially favors a viewpoint, after discussion the group consensus is likely a stronger endorsement of the viewpoint. Conversely, if the group was initially opposed to a viewpoint, group discussion would likely lead to stronger opposition.
34.3K
Stereotype Content Model02:16

Stereotype Content Model

14.7K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.7K
Social Proof00:52

Social Proof

27.7K
Social proof is a form of persuasion based on comparison and conformity. People compare their behavior and actions to what others are doing and will change to conform to do what their peers do.
27.7K
Confirmation Biases01:31

Confirmation Biases

5.5K
The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
5.5K
Groupthink01:34

Groupthink

44.4K
When in group settings, we are often influenced by the thoughts, feelings, and behaviors around us. Groupthink is another phenomenon of conformity where modification of the opinions of members in a group aligns with what they believe is the group consensus (Janis, 1972). In such situations, the group often takes action that individuals would not perform outside the group setting because groups make more extreme decisions than individuals do. Moreover, groupthink can hinder opposing trains of...
44.4K
In- and Out-Groups01:31

In- and Out-Groups

39.0K
People all belong to a gender, race, age, and social economic group. These groups provide a powerful source of our identity and self-esteem (Tajfel & Turner, 1979) and serve as our in-groups. An in-group is a group that we identify with or see ourselves as belonging to.
39.0K

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相关实验视频

Updated: Jul 8, 2025

Continuous Theta Burst Stimulation of the Posterior Medial Frontal Cortex to Experimentally Reduce Ideological Threat Responses
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Continuous Theta Burst Stimulation of the Posterior Medial Frontal Cortex to Experimentally Reduce Ideological Threat Responses

Published on: September 28, 2018

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基于协作过的推算法对意见两极分化的影响.

Alessandro Bellina1,2, Claudio Castellano2,3, Paul Pineau4

  • 1Dipartimento di Fisica Università "Sapienza," P. le A. Moro, 2, I-00185 Rome, Italy.

Physical review. E
|December 20, 2023
PubMed
概括

推算法塑造了在线用户体验. 这项研究揭示了协作过如何导致两极分化或共识,确定了没有过泡的个性化建议的条件.

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A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents
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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

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相关实验视频

Last Updated: Jul 8, 2025

Continuous Theta Burst Stimulation of the Posterior Medial Frontal Cortex to Experimentally Reduce Ideological Threat Responses
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Continuous Theta Burst Stimulation of the Posterior Medial Frontal Cortex to Experimentally Reduce Ideological Threat Responses

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A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents
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A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents

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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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科学领域:

  • 统计物理 统计物理
  • 计算社会科学 计算社会科学

背景情况:

  • 推算法通过策划内容显著影响在线用户体验.
  • 虽然对内容发现有好处,但这些算法可以创建过器泡,可能会增加社会两极分化.

研究的目的:

  • 调查用户-用户协作过推算法的对代理行为的影响.
  • 分析系统动态,特别是相似性和人气偏见如何影响用户行为和系统状态.

主要方法:

  • 分析和数值技术被用来模拟在重复暴露于算法的情况下的代理行为.
  • 根据相似性和人气偏差的强度,我们得出了一个相位图来映射系统状态.

主要成果:

  • 确定了三个不同的系统阶段:混乱,共识和两极分化.
  • 极化的特点是用户分裂成聚焦于单个项目的群体.
  • 在障碍极化边界发现了一个关键区域,可以实现非微不足道的个性化,而无需过气泡.
  • 该模型成功地复制了在last.fm音乐平台上观察到的用户行为模式.

结论:

  • 该研究为分析推算法提供了一个统计物理框架.
  • 研究结果表明,理解偏差参数对于减轻两极分化至关重要.
  • 这项研究为设计提供个性化内容的推系统开辟了道路,同时避免了过器泡和促进多样性.