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Social Media Sentiment Analysis Tool

Pricing

$1.50 / 1,000 Comments

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Social Media Sentiment Analysis Tool

Social Media Sentiment Analysis Tool

tri_angle/social-media-sentiment-analysis-tool

Developed by

Tri⟁angle

Maintained by Apify

Add a profile name and find this social profile on Facebook, Instagram, and TikTok, scrape its recent posts and comments, and perform sentiment analysis for each comment. All in one go. Export results in JSON, CSV, HTML, use API, schedule runs, integrate with other tools.

4.2 (7)

Pricing

$1.50 / 1,000 Comments

32

Monthly users

88

Runs succeeded

87%

Last modified

5 months ago

You can access the Social Media Sentiment Analysis Tool programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

1# Start Server-Sent Events (SSE) session and keep it running
2curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=tri_angle/social-media-sentiment-analysis-tool"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using 🤔 Social Media Sentiment Analysis Tool via Model Context Protocol (MCP) server

MCP server lets you use 🤔 Social Media Sentiment Analysis Tool within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the 🤔 Social Media Sentiment Analysis Tool Actor with the provided input.

1curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{
2  "jsonrpc": "2.0",
3  "id": 1,
4  "method": "tools/call",
5  "params": {
6    "arguments": {
7      "profileName": "Arnold Schwarzenegger"
8},
9    "name": "tri_angle/social-media-sentiment-analysis-tool"
10  }
11}'

The response should be: Accepted. You should received response via SSE (JSON) as:

1event: message
2data: {
3  "result": {
4    "content": [
5      {
6        "type": "text",
7        "text": "ACTOR_RESPONSE"
8      }
9    ]
10  }
11}

Configure local MCP Server via standard input/output for 🤔 Social Media Sentiment Analysis Tool

You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:

1{
2  "mcpServers": {
3    "actors-mcp-server": {
4      "command": "npx",
5      "args": [
6        "-y",
7        "@apify/actors-mcp-server",
8        "--actors",
9        "tri_angle/social-media-sentiment-analysis-tool"
10      ],
11      "env": {
12        "APIFY_TOKEN": "<YOUR_API_TOKEN>"
13      }
14    }
15  }
16}

You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.

To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.

Pricing

Pricing model

Pay per result 

This Actor is paid per result. You are not charged for the Apify platform usage, but only a fixed price for each dataset of 1,000 items in the Actor outputs.

Price per 1,000 items

$1.50