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Harvest Edge / Discord Message Sentiment

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Harvest Edge makes business information available to everyone!

🌼 Overview

The Discord Message Sentiment Scraper collects message data — including text, embeds, attachments, reactions, and mentions — and performs real-time sentiment analysis using the VADER Sentiment Analyzer.

This tool is designed for developers, data scientists, and analysts who need structured conversational data for research, analytics, or community insights.
It can scrape messages in either "older" or "newer" directions from a specific message ID, batching data safely to comply with Discord rate limits.

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🌾 Features

• 🧠 Sentiment analysis
• 📦 Structured output with message metadata, attachments, embeds, and reactions
• ⏱ Configurable batch delay to prevent API throttling
• 🔁 Directional scraping (newer or older)
• 🚫 Robust error handling with descriptive logs
• ⚙️ Optimized performance (fetches up to 10,000 messages per run)
• 💬 Works with Discord user tokens for full message access

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🔑 How to Get Your Discord Token

1. Open Developer Tools in your browser (F12 key) and go to discord.com/channels/@me
2. Click the Network tab and filter for Fetch/XHR
3. Refresh the page if needed and look for a request named @me
4. Under Request Headers, locate the Authorization field
5. Copy the long token string — that’s your Discord Token

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⚙️ Input Configuration

The Actor accepts the following input parameters via Apify:

Key	Type	Description	Default	Required
guild_id	String	The ID of the Discord server (guild) containing the target channel.	-	✅ Yes
channel_id	String	The ID of the channel from which to fetch messages.	-	✅ Yes
token	String	Your Discord user account token for authentication.	-	✅ Yes
max_messages	Integer	Maximum number of messages to fetch (1–10,000).	1000	❌ No
start_message_id	String	Optional message ID to start scraping from.	None	❌ No
scrape_direction	String	Direction of scrape: "newer" or "older".	newer	❌ No
batch_delay_seconds	String	Delay between message batches (in seconds, to manage rate limits).	1.0	❌ No

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🧾 Output Structure

Each message is output as a JSON object in your Apify dataset.

Field	Description
message_id	Unique message ID
channel_id	Channel ID
author	Object containing author details (id, username, discriminator, avatar, public_flags)
content	Text content of the message
timestamp	UTC timestamp of when the message was created
edited_timestamp	Timestamp if the message was edited
type	Discord message type (e.g., default, reply)
attachments	List of attachments (ID, filename, URL, size, etc.)
embeds	List of embeds (title, description, URL, thumbnail, etc.)
pinned	Boolean — whether message is pinned
mention_everyone	Boolean — whether the message mentions everyone
tts	Boolean — whether the message was text-to-speech
flags	Integer — Discord message flags
components	Array of UI components (e.g., buttons)
reactions	Array of reactions (emoji details, count, etc.)
mentions	Array of mentioned users (ID, username, discriminator)
message_reference	Object containing reply reference data
sentiment	Object with sentiment scores (pos, neu, neg, compound, label)

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🧠 Example Output

{
  "message_id": "123456789012345678",
  "channel_id": "987654321098765432",
  "author": {
    "id": "111222333444555666",
    "username": "example_user",
    "discriminator": "1234",
    "avatar": "https://cdn.discordapp.com/avatars/...png",
    "public_flags": 0
  },
  "content": "This is awesome!",
  "timestamp": "2025-10-20 14:30:00",
  "edited_timestamp": null,
  "attachments": [],
  "embeds": [],
  "pinned": false,
  "mention_everyone": false,
  "tts": false,
  "flags": 0,
  "components": [],
  "reactions": [],
  "mentions": [],
  "message_reference": null,
  "sentiment": {
    "compound": 0.8316,
    "pos": 0.7,
    "neu": 0.3,
    "neg": 0.0,
    "label": "positive"
  }
}