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相关概念视频

Data Collection by Survey01:07

Data Collection by Survey

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The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
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SBAR II: Application of SBAR01:14

SBAR II: Application of SBAR

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SBAR is an effective communication tool used by healthcare professionals to communicate patient information accurately. SBAR stands for Situation, Background, Assessment, and Recommendation. For a better understanding, an example is given below.
SBAR Report from a Nurse to a Health Care Provider
S: "Hello, Dr. Smith. This is Jane, RN, from the Med Surg unit. I am calling to tell you about Ms. White in Room 210, who is experiencing increased pain and redness at her incision site. Her recent...
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Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

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SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
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Stereotype Content Model02:16

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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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Attitudes01:54

Attitudes

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Attitude is our evaluation of a person, an idea, or an object. We have attitudes for many things ranging from products that we might pick up in the supermarket to people around the world to political policies. Typically, attitudes are favorable or unfavorable: positive or negative (Eagly & Chaiken, 1993). And, they have three components: an affective component (feelings), a behavioral component (the effect of the attitude on behavior), and a cognitive component (belief and knowledge;...
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Traits, Mood, and Subjective Wellbeing01:22

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Subjective well-being (SWB) refers to an individual's self-evaluation of their overall life satisfaction, happiness, and fulfillment. This multifaceted construct is typically assessed by analyzing the balance of positive and negative emotions alongside perceptions of life satisfaction. Personality traits such as neuroticism and extraversion are strongly associated with variations in SWB, offering critical insights into the underlying mechanisms of emotional well-being.
Neuroticism and...
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相关实验视频

Updated: Jun 11, 2025

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
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Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

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基于证券应用程序元素的用户情绪分析

Minji Kim1, Subeen Kim2, Yoonha Park2

  • 1Department of Artificial Intelligence, Kyung Hee University, Yongin 17104, Republic of Korea.

Behavioral sciences (Basel, Switzerland)
|September 28, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了基于方面的情绪分析 (ABSA),通过分析用户评论来改进韩国移动证券应用程序. ABSA揭示了特定用户对登录和交易等功能的反,提供了比传统方法更深入的设计见解.

关键词:
基于方面的情绪分析.证券申请 证券申请 证券申请用户评论 用户评论

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科学领域:

  • 自然语言处理自然语言处理.
  • 移动应用程序设计
  • 情绪分析 情绪分析

背景情况:

  • 由于复杂性,设计移动证券应用程序存在重大挑战.
  • 分析在线用户评论对于应用程序的改进至关重要.
  • 对韩国文本情感分析的深度学习应用尚未得到充分探索.

研究的目的:

  • 探索基于方面的情绪分析 (ABSA) 分析韩国证券申请审查.
  • 在这些应用程序中识别关键的设计元素和用户情绪.
  • 展示ABSA作为传统用户研究的可扩展和具有成本效益的替代方案.

主要方法:

  • 利用基于方面的情绪分析 (ABSA) 对韩国证券申请的基于文本的用户评论数据.
  • 应用的技术包括点向相互信息 (PMI),奇点值分解 (SVD) 和Word2Vec.
  • 确定了诸如"更新"",屏幕"",图表"",登录"",访问"",身份验证"",帐户"和"交易"等关键方面.

主要成果:

  • 与整体评级相比,ABSA对用户情绪提供了更深入的见解.
  • 确定了用户不满的特定领域,即使在一般积极的评论中也是如此.
  • 突出了影响移动证券应用程序用户体验的关键因素.

结论:

  • ABSA是一种有效的方法,用于在移动应用程序设计中揭示微妙的用户情绪.
  • 这种方法为证券应用领域的用户研究提供了一个可扩展和具有成本效益的解决方案.
  • 这些发现可以为移动证券平台的未来设计改进提供信息.