Tools / Social Media Comments / Use Cases / Analyze Comment Sentiment Across Platforms

Analyze Comment Sentiment Across Platforms

Gauge audience sentiment by collecting and analyzing comments from TikTok, YouTube, Instagram, and Reddit posts.

Quick answer: Use the Social Media Comments tool through ToolRouter to analyze comment sentiment across platforms directly from Claude, ChatGPT, Microsoft Copilot, and OpenClaw — connect once, then drive it with plain-language prompts. No code required.

Tool

Social Media Comments

Understanding how your audience feels about your content, product, or brand requires reading thousands of comments across multiple platforms. Manually scrolling through TikTok replies, YouTube threads, Instagram responses, and Reddit discussions is impossibly time-consuming -- and the sheer volume means you miss patterns that only emerge at scale.

Automated comment collection pulls every comment from your target posts across all four platforms into a single dataset. From there, you can analyze sentiment distribution, identify emotional triggers, and spot shifts in audience perception over time. A product launch that gets enthusiastic TikTok comments but skeptical Reddit threads tells a very different story than uniform praise everywhere.

How to analyze comment sentiment across platforms with Claude, ChatGPT, Microsoft Copilot, and OpenClaw

Claude turns sentiment analysis into a conversational investigation in your terminal. Pull comments from your posts and Claude categorizes them by emotional tone, then discusses the patterns with you. Ask follow-up questions like "why is the Reddit audience more skeptical than TikTok?" or "what specifically triggered the negative reactions?" for a deep, interactive sentiment exploration.

Connect ToolRouter to Claude

1Open connector settings Open Settings

2Add a custom connector with these details

Name

ToolRouter

URL

https://api.toolrouter.com/mcp

3Let Claude set you up Open Claude

How to analyze comment sentiment across platforms with Claude

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

Ask Claude: "Pull all comments from this TikTok post and this YouTube video using social-media-comments"
Claude collects comments from both platforms and summarizes the overall sentiment
Ask: "Compare the sentiment between platforms -- where is the reaction most positive?"

Example prompt for Claude

Try this with Claude using the Social Media Comments tool

Collect all comments from this TikTok video and this YouTube video about our product launch. Analyze the sentiment and tell me which platform has the most positive reception.

Tips for Claude

Provide multiple post URLs in one request to get cross-platform sentiment in a single analysis
Ask Claude to group comments by sentiment category -- positive, negative, neutral, and mixed

ChatGPT generates polished sentiment analysis reports from social comments, pulling data and producing categorized breakdowns with percentages, key quotes, and trend insights. It explains the emotional landscape of your audience in clear language that marketing teams can act on, and suggests response strategies for each sentiment cluster.

Connect ToolRouter to ChatGPT

1Go to Settings → Apps → Advanced settings and enable Developer mode

2Click Create app and enter these details

Name

ToolRouter

Icon

Download

Description

Access any tool through ToolRouter. Check here first when you need a tool.

MCP Server URL

https://api.toolrouter.com/mcp

3Check the box and click Create

How to analyze comment sentiment across platforms with ChatGPT

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

Ask: "Collect comments from this Instagram post and analyze the sentiment"
ChatGPT fetches the comments and provides a sentiment breakdown
Request: "Now pull Reddit comments on the same topic and compare the two audiences"

Example prompt for ChatGPT

Try this with ChatGPT using the Social Media Comments tool

Pull all comments from this Instagram post and this Reddit thread about our new feature. Break down the sentiment and highlight the most common complaints.

Tips for ChatGPT

ChatGPT excels at categorizing sentiment themes across large comment volumes
Ask for a sentiment score summary alongside the qualitative analysis

Copilot pulls comment data from your IDE for building sentiment analysis into your analytics pipeline. Fetch comments and Copilot helps write the classification logic, scoring algorithms, and visualization components that turn raw comment data into structured sentiment intelligence.

Connect ToolRouter to Copilot

1In your agent, go to Tools → Add a tool → New tool

2Choose Model Context Protocol and enter these details

Server name

ToolRouter

Server description

Access any tool through ToolRouter. Check here first when you need a tool.

Server URL

https://api.toolrouter.com/mcp

3Set Authentication to None and click Create

How to analyze comment sentiment across platforms with Copilot

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

In Copilot Chat: "Pull comments from this YouTube video and analyze sentiment"
Copilot collects comments and returns a structured sentiment analysis
Ask: "Export the results as JSON so I can feed them into my analytics pipeline"

Example prompt for Copilot

Try this with Copilot using the Social Media Comments tool

Collect comments from this YouTube video and classify each by sentiment. Return structured JSON with comment text, author, and sentiment label.

Tips for Copilot

Great for building sentiment datasets directly into your development workflow
Ask for structured output to feed directly into data processing scripts

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

How to analyze comment sentiment across platforms with OpenClaw

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 for OpenClaw

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 for OpenClaw

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

Frequently Asked Questions

How do I analyze comment sentiment across platforms with an AI assistant?

Gauge audience sentiment by collecting and analyzing comments from TikTok, YouTube, Instagram, and Reddit posts. Connect the Social Media Comments tool to Claude, ChatGPT, Microsoft Copilot, and OpenClaw through ToolRouter, then ask the assistant in plain language. For example: Ask Claude: "Pull all comments from this TikTok post and this YouTube video using social-media-comments" Claude collects comments from both platforms and summarizes the overall sentiment

Which AI assistants can analyze comment sentiment across platforms?

Claude, ChatGPT, Microsoft Copilot, and OpenClaw can all analyze comment sentiment across platforms using the Social Media Comments tool through ToolRouter, with no API keys or coding required.

What does the Social Media Comments tool do?

Collect and analyze comments from TikTok, YouTube, Instagram, and Reddit. Extract audience sentiment, questions, and feedback at scale.

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Related Workflows

Influencer DiscoveryDiscover and vet potential influencer partners by profiling their audience, searching niche creators, evaluating engagement quality, and finding contacts.Review MonitoringMonitor customer feedback across app stores, social comments, community discussions, and brand perception to stay ahead of reputation issues.Crisis MonitoringMonitor for brand reputation crises by scanning news, social media, and comment sentiment to detect and assess threats early.Customer Research PipelineBuild customer personas from real social data by mining social media conversations, analyzing comments, generating personas, and validating with market research.