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相关概念视频

Stereotype Content Model02:16

Stereotype Content Model

15.3K
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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Empathy02:34

Empathy

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Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor. 
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相关实验视频

Updated: May 2, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
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Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

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一个基于机器学习的同理心映射框架,通过应用程序审查分析来增强用户体验.

Faryal Ishfaq1, Safdar Nawaz Khan Marwat2,3, Waseem Ullah Khan2,3

  • 1Department of Computer Science, University of Peshawar, Peshawar, Pakistan.

Scientific reports
|December 2, 2025
PubMed
概括
此摘要是机器生成的。

这项研究自动化了用户体验 (UX) 共感映射,使用变压器 (BERT) 的双向编码器表示和应用程序评价上的隐性迪里克莱特分配 (LDA). 这种数据驱动的方法提高了用户体验设计研究的可扩展性和效率.

关键词:
应用程序审查采矿贝尔特 (BERT) 公司深度学习是一种深度学习.共感映射的绘制.自然语言处理 (NLP)情绪分析是一种情绪分析.软件工程 软件工程 软件工程文字分类 文本分类 文本分类主题建模 主题建模用户体验用户体验.

相关实验视频

Last Updated: May 2, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
07:14

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

1.1K

科学领域:

  • 人与计算机的交互
  • 软件工程 软件工程 软件工程
  • 自然语言处理自然语言处理.

背景情况:

  • 用户体验 (UX) 对软件的有效性至关重要,它会影响用户的参与度和满意度.
  • 共感映射是一种设计思维技术,有助于理解用户的感知,但传统上是手动的,耗时和昂贵的.
  • 现有的方法限制了用户体验研究和设计过程的可扩展性.

研究的目的:

  • 利用用户发布的应用程序评论开发一种用于同情心映射的自动化流程.
  • 提高用户体验设计和研究的效率和可扩展性.
  • 以利用自然语言处理为数据驱动的用户体验洞察力.

主要方法:

  • 使用变压器双向编码器表示 (BERT) 的情感分析来将评论分为积极的 (收益) 和消极的 (痛苦).
  • 使用隐藏的迪里克莱特分配 (LDA) 进行主题建模,以识别用户偏好和评论中的关键主题.
  • 应用程序评论的自动分析取代了传统的手动同理心映射技术.

主要成果:

  • 拟议的BERT模型在情绪分类中实现了高准确度,训练二元准确度达到98.61% (精度97.82%,F1 98.62%,回忆99.42%).
  • 验证精度达到了92.58% (F1 92.59%,精度 92.43%,回忆 92.75%),显示出强大的性能.
  • 自动化方法在效率和可扩展性方面显著改善了传统的手动同情心映射.

结论:

  • 自动化同情心映射过程为传统方法提供了可扩展和高效的替代方案.
  • 这种数据驱动的方法为用户体验设计团队和开发人员提供了宝贵的见解.
  • 该模型促进了快速的用户反,使软件应用程序的持续改进成为可能.