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Stereotype Content Model02:16

Stereotype Content Model

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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...
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相关实验视频

Updated: Jul 10, 2025

Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios
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人机交互的结构化数据集,使适应性用户界面成为可能.

Angela Carrera-Rivera1, Daniel Reguera-Bakhache2, Felix Larrinaga2

  • 1Faculty of Engineering, Electronics, and Computing. Mondragon Unibertsitatea, Arrasate-Mondragon, 20500, Spain. aicarrera@mondragon.edu.

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|November 25, 2023
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概括
此摘要是机器生成的。

一个新的数据集捕捉了人机交互,以帮助自适应的人机界面 (HMI) 的开发. 这些结构化数据为界面设计和分析提供了对用户行为的洞察.

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科学领域:

  • 计算机科学 计算机科学
  • 人与计算机的交互
  • 数据科学数据科学数据科学

背景情况:

  • 人机界面 (HMI) 对于用户交互至关重要.
  • 开发适应性HMI需要全面的用户行为数据.
  • 现有的数据集可能缺乏用于高级HMI开发所需的结构化细节.

研究的目的:

  • 介绍一个关于人机交互的新型数据集.
  • 促进适应性人机接口 (HMI) 的发展.
  • 为用户界面适应提供对用户行为的见解.

主要方法:

  • 采集的交互数据使用一个定制的应用程序与正式定义的用户界面 (UI).
  • 处理和分析交互数据,包括清理和确保一致性.
  • 进行数据分析,以验证相互作用序列的一致性.

主要成果:

  • 创建了一个人机交互的结构化数据集.
  • 数据集适合专业人士和数据分析师专注于UI适应.
  • 相关的数据收集和分析的代码是公开的.

结论:

  • 该数据集为HMI研发提供了宝贵的资源.
  • 数据和代码的可用性支持了自适应用户界面的进步.
  • 能够更深入地理解和利用用户交互模式.