Social Sentiment — 技能 — openclaw中文资讯站

技能详情（站内镜像，无评论）

Sentiment analysis for brands and products across Twitter, Reddit, and Instagram. Monitor public opinion, track brand reputation, detect PR crises, surface complaints and praise at scale — analyze 70K+ posts with bulk CSV export and Python/pandas. Social listening and brand mo…

开发与 DevOps

许可证：MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本：v1.4.0

统计：⭐ 4 · 3k · 11 current installs · 11 all-time installs

⭐ 4

安装量（当前） 11

🛡 VirusTotal ：可疑 · OpenClaw ：可疑

Package：atyachin/social-sentiment

安全扫描（ClawHub）

VirusTotal ：可疑
OpenClaw ：可疑

OpenClaw 评估

The skill's purpose (social sentiment via Xpoz API) mostly matches its instructions, but the registry metadata, runtime instructions, and install/credential expectations are inconsistent and need clarification before trusting it.

目的

Name and description align with using an xpoz API client (mcporter) to fetch social posts and then analyze CSVs locally. Requiring a CLI named 'mcporter' and describing queries + CSV export is coherent for this purpose.

说明范围

SKILL.md instructs the agent to run an external 'xpoz-setup' skill for OAuth and to call mcporter commands against mcp.xpoz.ai and to download large CSVs to local paths. The top-level registry metadata omitted the 'xpoz-setup' dependency and the credential/network requirements shown in SKILL.md, creating a mismatch about what the agent will do and what it needs.

安装机制

Install uses npm to install the 'mcporter' package and create a 'mcporter' binary. npm installs are common but carry moderate risk — the package should be audited (publisher, popularity, code) before installation. No arbitrary URL downloads or archive extraction are present.

证书

Registry metadata lists no required credentials, but SKILL.md explicitly requires an Xpoz account and OAuth via the xpoz-setup skill and network access to mcp.xpoz.ai. OAuth tokens and any account credentials are sensitive; the inconsistency between declared and actual credential requirements is a red flag and should be clarified.

持久

The skill is not marked 'always: true' and does not request system-wide changes. It delegates authentication to another skill (xpoz-setup) rather than storing credentials itself. No evidence it modifies other skills or agent configs.

安装（复制给龙虾 AI）

将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Social Sentiment」。简介：Sentiment analysis for brands and products across Twitter, Reddit, and Instagra…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/atyachin/social-sentiment/SKILL.md
（来源：yingzhi8.cn 技能库）

SKILL.md

打开原始 SKILL.md（GitHub raw）

---
name: social-sentiment
description: "Sentiment analysis for brands and products across Twitter, Reddit, and Instagram. Monitor public opinion, track brand reputation, detect PR crises, surface complaints and praise at scale — analyze 70K+ posts with bulk CSV export and Python/pandas. Social listening and brand monitoring powered by 1.5B+ indexed posts."
homepage: https://xpoz.ai
metadata:
  {
    "openclaw":
      {
        "requires":
          {
            "bins": ["mcporter"],
            "skills": ["xpoz-setup"],
            "network": ["mcp.xpoz.ai"],
            "credentials": "Xpoz account (free tier) — auth via xpoz-setup skill (OAuth 2.1)",
          },
        "install": [{"id": "node", "kind": "node", "package": "mcporter", "bins": ["mcporter"], "label": "Install mcporter (npm)"}],
      },
  }
tags:
  - sentiment-analysis
  - brand-monitoring
  - social-media
  - twitter
  - reddit
  - instagram
  - analytics
  - brand-sentiment
  - reputation
  - social-listening
  - opinion-mining
  - brand-tracking
  - competitor-analysis
  - public-opinion
  - crisis-detection
  - NLP
  - reputation
  - mcp
  - xpoz
  - opinion
  - market-research
---

# Social Sentiment

**Analyze brand sentiment from live social conversations at scale.**

Surfaces themes, flags viral complaints, compares competitors. Analyzes 1K-70K posts via bulk CSV + Python.

## Setup

Run `xpoz-setup` skill. Verify: `mcporter call xpoz.checkAccessKeyStatus`

## 4-Step Process

### Step 1: Search Platforms

Queries: (1) `"Brand"` (2) `"Brand" AND (slow OR buggy)` (3) `"Brand" AND (love OR amazing)`

```bash
mcporter call xpoz.getTwitterPostsByKeywords query='"Notion"' startDate="YYYY-MM-DD"
mcporter call xpoz.checkOperationStatus operationId="op_..." # Poll 5s
```

Repeat for Reddit/Instagram. Default: 30 days.

### Step 2: Download CSVs

Use `dataDumpExportOperationId`, poll with `checkOperationStatus` for download URL (up to 64K rows).

### Step 3: Analyze

Python/pandas:

```python
import pandas as pd
df = pd.read_csv('/tmp/twitter-sentiment.csv')

POSITIVE = ['love', 'amazing', 'best', 'recommend']
NEGATIVE = ['hate', 'terrible', 'worst', 'broken']

def classify(text):
    t = str(text).lower()
    pos = sum(1 for k in POSITIVE if k in t)
    neg = sum(1 for k in NEGATIVE if k in t)
    return 'positive' if pos>neg else ('negative' if neg>pos else 'neutral')

df['sentiment'] = df['text'].apply(classify)
```

Extract themes, find viral by engagement. Customize keywords.

### Step 4: Report

```
Sentiment: 72/100 | Posts: 14,832
😊 58% | 😠 24% | 😐 18%

Themes: Performance (2K, 81% neg), UX (1.8K, 72% pos)
Viral: [Top 10]
```

Score: Engagement-weighted, 0-100. Include insights.

## Tips

Download full CSVs | Reddit = honest | Store `data/social-sentiment/` for trends