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reddit-thread-analyzer

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Reddit Thread Analyzer

Reddit帖子分析器

Extract deep insights from Reddit discussions including sentiment, key arguments, and community consensus.
When a user provides a Reddit thread URL or asks about Reddit opinions, analyze the discussion comprehensively to surface meaningful patterns and insights.
从Reddit讨论中提取深度洞察，包括情感倾向、核心论点和社区共识。
当用户提供Reddit帖子URL或询问Reddit社区观点时，全面分析讨论内容，挖掘有意义的模式和洞察。

Instructions

使用说明

1. Fetch and Parse Thread Data

1. 获取并解析帖子数据

Use WebFetch to load the Reddit thread and extract:
  • Post title, body, author, score, and timestamp
  • All comments (not just top-level)
  • Comment scores, awards, and timestamps
  • Note verified contributors or expert flair
使用WebFetch加载Reddit帖子并提取：
  • 帖子标题、正文、作者、评分和时间戳
  • 所有评论（不仅限于顶层评论）
  • 评论评分、奖励和时间戳
  • 标记经过验证的贡献者或专家标识

2. Analyze Overall Sentiment

2. 分析整体情感倾向

Determine the dominant sentiment and emotional tone:
  • Overall sentiment: Positive, negative, neutral, or mixed
  • Sentiment distribution: Approximate percentages
  • Emotional tone: Excited, frustrated, skeptical, supportive, angry, enthusiastic
  • Shift over time: Note if sentiment changes throughout discussion
确定主导情感和情绪基调：
  • 整体情感：正面、负面、中立或混合
  • 情感分布：大致占比
  • 情绪基调：兴奋、沮丧、怀疑、支持、愤怒、热情
  • 随时间变化：记录讨论过程中情感是否发生变化

3. Extract Key Arguments

3. 提取核心论点

Identify the most impactful points:
Top Arguments in Favor (3-5 points):
  • Quote the argument
  • Note comment score
  • Identify supporting evidence or reasoning
Top Arguments Against (3-5 points):
  • Quote the argument
  • Note comment score
  • Identify counter-points and rebuttals
Expert or Verified Opinions:
  • Highlight comments from verified experts
  • Note OP responses and clarifications
识别最具影响力的观点：
核心支持论点（3-5条）：
  • 引用论点原文
  • 标记评论评分
  • 标注支持性证据或推理
核心反对论点（3-5条）：
  • 引用论点原文
  • 标记评论评分
  • 标注反驳观点和回应
专家或验证用户观点：
  • 突出经过验证的专家评论
  • 记录原帖发布者（OP）的回复和澄清内容

4. Find Consensus Points

4. 识别共识点

Determine what the community agrees on:
  • Points with broad agreement (high scores, no controversy)
  • Emerging patterns across multiple comments
  • Common ground between opposing viewpoints
确定社区达成共识的内容：
  • 获得广泛认同的观点（高评分、无争议）
  • 多条评论中呈现的共性模式
  • 对立观点之间的共同点

5. Identify Controversial Topics

5. 标记争议话题

Flag heavily debated points:
  • Topics with mixed upvotes/downvotes
  • Arguments that sparked long comment chains
  • Divisive issues where community is split
标记争议性强的观点：
  • 赞踩两极分化的话题
  • 引发长评论链的争论点
  • 社区意见严重分裂的问题

6. Provide Structured Analysis

6. 提供结构化分析报告

Format your analysis clearly:
markdown
undefined
清晰格式化分析内容：
markdown
undefined

Reddit Analysis: [Thread Title]

Reddit Analysis: [Thread Title]

Executive Summary

Executive Summary

[2-3 sentence overview of the discussion and main takeaway]
[2-3 sentence overview of the discussion and main takeaway]

Overall Sentiment

Overall Sentiment

  • Dominant Sentiment: Positive/Negative/Neutral/Mixed (X%)
  • Emotional Tone: [excited/frustrated/skeptical/etc.]
  • Community Alignment: High/Medium/Low
  • Dominant Sentiment: Positive/Negative/Neutral/Mixed (X%)
  • Emotional Tone: [excited/frustrated/skeptical/etc.]
  • Community Alignment: High/Medium/Low

Top Arguments

Top Arguments

In Favor

In Favor

  1. [Main point] (+XXX score)
    "[Direct quote from comment]"
    • [Brief explanation of reasoning]
  2. [Main point] (+XXX score)
    "[Direct quote]"
  1. [Main point] (+XXX score)
    "[Direct quote from comment]"
    • [Brief explanation of reasoning]
  2. [Main point] (+XXX score)
    "[Direct quote]"

Against

Against

  1. [Main point] (+XXX score)
    "[Direct quote]"
  1. [Main point] (+XXX score)
    "[Direct quote]"

Community Consensus

Community Consensus

  • ✅ [Point most people agree on]
  • ✅ [Another consensus point]
  • ✅ [Point most people agree on]
  • ✅ [Another consensus point]

Controversial Topics

Controversial Topics

  • ⚠️ [Divisive issue] - Community split roughly 50/50
  • ⚠️ [Another debate point]
  • ⚠️ [Divisive issue] - Community split roughly 50/50
  • ⚠️ [Another debate point]

Notable Insights

Notable Insights

  • Expert Opinion: [Quote from verified expert] (+XXX)
  • Surprising Take: [Unexpected perspective that gained traction]
  • Most Helpful: [Most practical or actionable advice]
  • Expert Opinion: [Quote from verified expert] (+XXX)
  • Surprising Take: [Unexpected perspective that gained traction]
  • Most Helpful: [Most practical or actionable advice]

Key Quotes

Key Quotes

"[Memorable quote]" - u/username (+XXX score) "[Another impactful quote]" - u/username (+XXX score)
"[Memorable quote]" - u/username (+XXX score) "[Another impactful quote]" - u/username (+XXX score)

Discussion Quality

Discussion Quality

  • Civility: High/Medium/Low
  • Depth: Superficial/Moderate/Deep
  • Evidence-based: Yes/No/Mixed
undefined
  • Civility: High/Medium/Low
  • Depth: Superficial/Moderate/Deep
  • Evidence-based: Yes/No/Mixed
undefined

Best Practices

最佳实践

  • Focus on highly upvoted comments for consensus
  • Include exact scores to show community agreement level
  • Quote directly rather than paraphrasing
  • Preserve nuance - avoid oversimplifying complex debates
  • Note OP responses - original poster often adds important context
  • Distinguish facts from opinions clearly
  • Highlight constructive vs. unproductive discussions
  • Consider recency - early comments may be less informed than later ones
  • 重点关注高赞评论以识别共识
  • 包含准确评分以体现社区认同度
  • 直接引用原文而非意译
  • 保留细节差异 - 避免过度简化复杂争论
  • 记录原帖发布者（OP）的回复 - 原作者通常会补充重要背景信息
  • 明确区分事实与观点
  • 区分建设性讨论与无效讨论
  • 考虑时效性 - 早期评论可能不如后期评论信息全面

Example Analysis

示例分析

User: "What does Reddit think about the new iPhone?"
Your analysis:
  1. Fetch r/apple or r/iPhone thread
  2. Analyze 300+ comments
  3. Determine sentiment: Mixed (55% positive, 45% negative)
  4. Extract top pros: Camera improvements (+450), Performance (+380)
  5. Extract top cons: High price (+420), Incremental updates (+390)
  6. Note consensus: Good phone, but expensive for what you get
  7. Identify controversy: Whether it's worth upgrading from iPhone 14
  8. Surface expert opinions from tech reviewers
  9. Deliver structured report with quotes and scores
Remember: Focus on substance over noise. Prioritize well-reasoned arguments over emotional reactions.
用户：“Reddit社区对新款iPhone的看法是什么？”
你的分析：
  1. 获取r/apple或r/iPhone版块的帖子
  2. 分析300+条评论
  3. 确定情感倾向：混合（55%正面，45%负面）
  4. 提取核心优势：相机提升（+450赞）、性能表现（+380赞）
  5. 提取核心劣势：价格过高（+420赞）、升级幅度小（+390赞）
  6. 记录共识：手机本身不错，但性价比低
  7. 识别争议点：从iPhone 14升级是否值得
  8. 呈现科技评论者的专家观点
  9. 交付包含引用和评分的结构化报告
注意：聚焦实质内容，而非无关噪音。优先考虑有理有据的论点，而非情绪化反应。