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comment-mining

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🇺🇸

Original

English
🇨🇳

Translation

Chinese

Comment Mining

评论挖掘

Overview

概述

Mine public comments for what people actually ask, complain about, want, misunderstand, or repeat. The output should help with product research, content ideas, copywriting, objection handling, and audience understanding.
挖掘公开评论，了解人们实际提出的问题、抱怨的内容、需求、误解点或反复提及的信息。输出结果应能为产品调研、内容创意、文案撰写、异议处理以及受众理解提供支持。

When to Use

适用场景

Use this skill when the user asks to:
  • analyze comments on a TikTok, YouTube video, Instagram Reel, Facebook post, Reddit post, or Rumble video
  • find audience questions, objections, complaints, or buying intent
  • extract voice-of-customer language
  • find content ideas from comments
  • understand sentiment around a post, creator, product, or topic
当用户提出以下需求时，使用此技能：
  • 分析TikTok、YouTube视频、Instagram Reel、Facebook帖子、Reddit帖子或Rumble视频的评论
  • 查找受众的问题、异议、投诉或购买意向
  • 提取客户声音用语
  • 从评论中寻找内容创意
  • 了解帖子、创作者、产品或话题相关的情绪倾向

Comment Sources

评论来源

PlatformEndpoint
TikTok comments
/v1/tiktok/video/comments
TikTok replies
/v1/tiktok/video/comment/replies
YouTube comments
/v1/youtube/video/comments
YouTube replies
/v1/youtube/video/comment/replies
Instagram comments
/v2/instagram/post/comments
Facebook comments
/v1/facebook/post/comments
Facebook replies
/v1/facebook/post/comment/replies
Reddit comments
/v1/reddit/post/comments
Rumble comments
/v1/rumble/video/comments
平台接口（Endpoint）
TikTok评论
/v1/tiktok/video/comments
TikTok回复
/v1/tiktok/video/comment/replies
YouTube评论
/v1/youtube/video/comments
YouTube回复
/v1/youtube/video/comment/replies
Instagram评论
/v2/instagram/post/comments
Facebook评论
/v1/facebook/post/comments
Facebook回复
/v1/facebook/post/comment/replies
Reddit评论
/v1/reddit/post/comments
Rumble评论
/v1/rumble/video/comments

Workflow

工作流程

  1. Fetch comments
    • Use the post/video URL whenever possible.
    • Paginate when the endpoint supports it and the user wants depth.
    • Preserve comment text, author if public, like/upvote count, timestamp, and source URL.
  2. Clean lightly
    • Remove obvious spam/duplicates.
    • Keep slang, misspellings, and emotional wording if it is useful customer language.
    • Do not over-normalize exact quotes.
  3. Classify each useful comment Use these buckets:
    • questions
    • objections
    • complaints/pain points
    • praise
    • confusion
    • requests/feature ideas
    • buying intent
    • controversy/debate
    • jokes/memes/culture signals
  4. Cluster themes
    • Group similar comments.
    • Score themes by frequency and intensity.
    • Highlight exact quotes for each theme.
  5. Turn insights into actions Depending on the user's goal, produce:
    • content ideas
    • FAQ ideas
    • landing page copy angles
    • product ideas
    • objection-handling bullets
    • sales/support notes
  1. 获取评论
    • 尽可能使用帖子/视频的URL。
    • 当接口支持分页且用户需要深入数据时，进行分页获取。
    • 保留评论文本、公开的作者信息、点赞/顶帖数、时间戳以及来源URL。
  2. 轻度清洗
    • 删除明显的垃圾信息/重复内容。
    • 如果俚语、拼写错误和情绪化表述属于有用的客户用语，则予以保留。
    • 不要过度规范精确引用的内容。
  3. 对每条有用评论进行分类 使用以下分类：
    • 问题
    • 异议
    • 投诉/痛点
    • 赞扬
    • 困惑
    • 请求/功能创意
    • 购买意向
    • 争议/辩论
    • 笑话/梗/文化信号
  4. 主题聚类
    • 将相似评论分组。
    • 根据出现频率和强度为主题打分。
    • 突出每个主题的精确引用内容。
  5. 将洞察转化为行动 根据用户目标生成以下内容：
    • 内容创意
    • FAQ创意
    • 着陆页文案角度
    • 产品创意
    • 异议处理要点
    • 销售/支持笔记

Output Format

输出格式

markdown
undefined
markdown
undefined

Comment Mining Report

Comment Mining Report

Summary

Summary

  • Source(s): {urls}
  • Comments analyzed: {count}
  • Confidence: High/Medium/Low
  • Source(s): {urls}
  • Comments analyzed: {count}
  • Confidence: High/Medium/Low

Top Themes

Top Themes

ThemeTypeFrequencyIntensityRepresentative quote
ThemeTypeFrequencyIntensityRepresentative quote

Audience Questions

Audience Questions

  • "..."
  • "..."

Objections and Concerns

Objections and Concerns

  • Objection: ...
    • Evidence: "..."
    • Response angle: ...
  • Objection: ...
    • Evidence: "..."
    • Response angle: ...

Buying Intent / Demand Signals

Buying Intent / Demand Signals

  • "..."
  • "..."

Exact Language to Reuse

Exact Language to Reuse

  • "..."
  • "..."
  • "..."
  • "..."

Content Ideas From Comments

Content Ideas From Comments

  1. ...
  2. ...
undefined
  1. ...
  2. ...
undefined

Quality Guardrails

质量准则

  • Label sample size and confidence.
  • Separate one loud comment from a repeated pattern.
  • Preserve exact quotes for useful language.
  • Avoid claiming broad market sentiment from one post's comments.
  • Call out moderation/platform bias when relevant.
  • 标注样本量和置信度。
  • 将单个尖锐评论与重复出现的模式区分开。
  • 保留有用用语的精确引用。
  • 避免根据单个帖子的评论就断言广泛的市场情绪。
  • 相关时指出审核/平台偏见。

Common Pitfalls

常见误区

  • Do not flatten comments into generic sentiment. The value is in questions, objections, and exact wording.
  • Do not include personally identifying details unless they are already public and necessary.
  • Do not treat bot/spam comments as audience signal.
  • Do not skip Reddit post context. For Reddit, read both the original post and comments.
  • 不要将评论简化为通用情绪。核心价值在于问题、异议和精确表述。
  • 除非信息已公开且必要，否则不要包含个人识别信息。
  • 不要将机器人/垃圾评论视为受众信号。
  • 不要忽略Reddit帖子的上下文。对于Reddit，需同时阅读原帖和评论。