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social-listening-brief

面向品牌、人物、产品或话题的公开社交媒体讨论研究，按主题聚类并区分正负中性及混合情绪，保留来源、日期、互动指标和原文引用，输出含执行摘要、代表性帖子、风险机会与建议行动的简报；明确说明并非穷尽式社媒监控。

ScrapeCreators
热度 0.00
最近更新 2026-10-19 01:43:29
分类：营销依赖：代码执行 / 读写文件 / 联网浏览搜索 / 第三方 API应用场景：社交媒体 / 市场分析 / 研究 / 报告撰写 ...

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add scrapecreators/social-media-research-skills/social-listening-brief
Metadata
name
social-listening-brief
description
Use when the user wants a social listening report about what people are saying about a brand, person, product, topic, category, or niche across public social platforms. Produces cited themes, sentiment caveats, notable posts, and recommended actions.
allowed-tools
Bash, Read, Write, WebFetch
version
1.0.0
author
ScrapeCreators
license
MIT
homepage
https://scrapecreators.com
repository
https://github.com/ScrapeCreators/social-media-research-skills
metadata
{"openclaw":{"requires":{"env":["SCRAPECREATORS_API_KEY"]},"primaryEnv":"SCRAPECREATORS_API_KEY","homepage":"https://scrapecreators.com","tags":["social-media","research","scrapecreators"]}}

Social Listening Brief

Overview

Research what people are saying publicly across social platforms. This is useful for brand monitoring, category research, product feedback, reputation checks, and understanding recent conversations.

When to Use

Use this skill when the user asks:

  • what are people saying about X?
  • monitor this brand/topic/category
  • find complaints or praise about a product
  • summarize recent social discussion
  • compare sentiment across Reddit, TikTok, YouTube, LinkedIn, Instagram, or Threads

Useful Sources

  • Reddit search, subreddit search, posts, comments
  • TikTok search top/keyword/hashtag and comments
  • YouTube search, transcripts, comments
  • Instagram reels search and hashtag search
  • LinkedIn post search
  • Threads search
  • Google search when platform search is not enough

Workflow

  1. Define topic, aliases, competitor names, and date window.
  2. Search multiple relevant sources, not every source blindly.
  3. Keep URLs, dates, platform, engagement metrics, and exact quotes.
  4. Cluster conversations into themes.
  5. Separate positive, negative, neutral, and mixed signals.
  6. Highlight representative examples and action items.

Output Format

# Social Listening Brief: {topic}

## Executive Summary
- Main takeaway:
- Conversation volume: Low/Medium/High
- Sentiment: Positive/Neutral/Negative/Mixed
- Confidence: High/Medium/Low

## Top Themes
| Theme | Sentiment | Evidence | Representative quote/source |
|---|---|---|---|

## Notable Posts
- [source](url) — why it matters

## Risks / Opportunities
- ...

## Recommended Actions
1. ...

Common Pitfalls

  • Do not pretend this is exhaustive social monitoring. It is public-data research.
  • Do not average sentiment across very different communities without caveats.
  • Do not use engagement as a proxy for truth.