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How to Analyze Comment Sentiment with OpenClaw

Comment sentiment analysis with OpenClaw and ToolRouter. Cross-platform social media insights.

OpenClaw automates cross-platform sentiment analysis by batch-pulling comments from multiple posts simultaneously and producing structured sentiment datasets. Output includes per-comment sentiment labels, aggregate scores per post, and platform comparison metrics. Feed directly into your analytics database for longitudinal sentiment tracking.

Connect ToolRouter to OpenClaw

1Install the CLI

npm install -g toolrouter-mcp

2Call tools directly from OpenClaw

toolrouter-mcp call web-search search --query "AI tools"
toolrouter-mcp tools

Steps

Once connected (see setup above), use the Social Media Comments tool:

Ask OpenClaw: "Collect comments from this TikTok video and analyze the sentiment"
OpenClaw fetches comments and provides sentiment analysis
Ask: "What are the top three sentiment themes in these comments?"

Example Prompt

Try this with OpenClaw using the Social Media Comments tool

Pull all comments from this TikTok video and this YouTube video. Analyze the overall sentiment and identify the dominant emotional themes.

Tips

Combine results from multiple platforms in one session for a unified sentiment view
Ask for a comparison of sentiment distribution across different post types

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