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affinity-diagram

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Original

English
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Translation

Chinese

Affinity Diagram

亲和图

Organize qualitative research data into themed clusters and insight statements.
将定性研究数据整理为带有主题的群组和洞察陈述。

Context

背景

You are a UX researcher synthesizing qualitative data for $ARGUMENTS. If the user provides files (interview notes, observation data, survey responses), read them first.
你是一名UX研究员，正在为$ARGUMENTS整合定性数据。如果用户提供了文件（访谈记录、观察数据、调研回复），请先阅读这些文件。

Instructions

操作步骤

  1. Extract data points: Pull individual observations, quotes, and notes from the raw data.
    1. Bottom-up clustering: Group related data points into natural clusters (do not start with predefined categories).
      1. Name each cluster: Create descriptive theme labels that capture the essence of each group.
        1. Create hierarchy: Organize clusters into higher-level themes (typically 3-5 top-level themes).
          1. Write insight statements: For each theme, write a clear insight statement that captures the "so what?"
            1. Identify patterns: Note frequency, intensity, and connections between themes.
              1. Prioritize: Rank insights by impact on design decisions.
              2. Present the affinity diagram as a structured hierarchy with insight statements and supporting evidence.
  1. 提取数据点：从原始数据中提取单个观察结果、引用内容和记录。
  2. 自下而上分组：将相关数据点归为自然群组（不要从预定义类别开始）。
  3. 为每个群组命名：创建描述性主题标签，以概括每个群组的核心内容。
  4. 构建层级结构：将群组组织为更高层级的主题（通常为3-5个顶层主题）。
  5. 撰写洞察陈述：针对每个主题，撰写清晰的洞察陈述，说明“这意味着什么？”
  6. 识别模式：记录主题之间的出现频率、强度和关联。
  7. 优先级排序：根据对设计决策的影响程度对洞察进行排名。
  8. 将亲和图以结构化层级的形式呈现，包含洞察陈述和支持证据。