Reddit and X (Formerly Twitter) integration

Description This workflow provides a powerful AI assistant for content creators, book editors, and marketers. It automates the collection and analysis of trending discussions from Reddit, YouTube, and X (Twitter), generating insightful topic reports. This frees you from hours of tedious data compilation, allowing you to make faster, more accurate topic decisions based on deep AI analysis. How it works This workflow simulates the complete research process of a strategic editor: Initiate & Collect: A user submits a keyword via a public Form Trigger. The workflow then automatically fetches relevant, trending content in parallel from the official APIs of Reddit, YouTube, and X (Twitter). Multi-stage AI Processing & Analysis: The workflow utilizes a layered AI pipeline to process the data. First, a lightweight Gemini model in the AI Pre-filter Content node rapidly screens the vast amount of content to filter out noise. Next, a more powerful Gemini Pro model in the AI Deep Analysis node performs a detailed, structured analysis on each high-value item, extracting summaries, sentiment, and key arguments. Finally, a "strategist" AI model in the AI Synthesize Final Report node aggregates all analyses to generate the comprehensive final topic report in HTML. Multi-Channel Report Distribution: The workflow distributes the final report to multiple channels based on pre-defined templates. The Send Gmail Report node sends the complete HTML report. The Send Feishu Notification node sends a concise summary card to a group chat. Meanwhile, the Archive to Google Sheets node archives key data. Setup Steps This workflow takes approximately 20-30 minutes to set up, with most of the time spent connecting your accounts. Connect Your API Accounts: In the n8n Credentials section, you will need to prepare and connect credentials for the following services: Google: For the Gemini AI model, Gmail sending, and Google Sheets archiving. This requires a Google Cloud API Key and OAuth2 credentials. Reddit: For fetching Reddit posts. This requires a Reddit account with OAuth2 configured in n8n to allow searches. YouTube: For collecting YouTube videos. You'll need to enable the YouTube Data API v3 in your Google Cloud Console and get an API Key. Twitter: For the official Twitter node, requiring a free developer account and an App with v2 API access. Configure Output Channels: In the final nodes (Send Gmail Report, Send Feishu Notification, Archive to Google Sheets), update the recipient email address, the Feishu bot's Webhook URL, and the target spreadsheet ID to match your own. Activate and Share the Trigger: Activate the workflow. The first Form Trigger node will automatically generate a public URL. Share this link with your team members to let them start using the tool.

WATCH THE n8n STARTER GUIDE 👇 This template is featured in the n8n Starter Guide series. The template is free, but comes with two additional PDFs and a Quick Start video if you grab the full download pack on gumroad. How it works This template is a visual map of many useful n8n nodes. It groups nodes like Triggers, AI tools, and App connectors onto the canvas. Explore the sections to learn about different nodes and easily copy them for your own workflows. It acts as a handy visual reference guide. Set up steps • Setup takes about 5 minutes. • Import the template into your n8n instance. • Explore the node categories visually on the canvas. • A Quick Start video is included in the download pack, along with a prompts PDF and PDF with links to other awesome n8n templates here on the n8n template gallery.

Turn your blog into a set-and-forget content engine: every new article is instantly repurposed into channel-specific social posts with visuals, keeping your brand visible on LinkedIn, X, and Reddit without extra copywriting time. Perfect for lean marketing teams who want consistent, always-on distribution from a single source of content. How it works • Watches your blog RSS feed (or receives a single URL) and detects new articles. • Saves each post in Postgres so every article is only processed once. • Fetches the article HTML, extracts the main body content and sends it to OpenAI (GPT-4.1). • OpenAI creates platform-optimized copy: 1 LinkedIn post, 1 X/Twitter post, 1 Reddit post + image prompts. • Generates on-brand images with OpenAI and publishes everything automatically to LinkedIn, X, and Reddit. • You can also trigger it manually or via webhook whenever you want to push a specific campaign. Setup Steps • Time: around 20–40 minutes for someone familiar with n8n and the platforms. • Create a Postgres table “rss_items” with fields: guid (PRIMARY KEY), title, link, published_at. • Add credentials in n8n for: – Postgres – OpenAI – LinkedIn OAuth2 – X/Twitter OAuth2 + OAuth1 (for media upload) – Reddit OAuth2 • In the RSS node, set your blog feed URL (for example: https://yourblog.com/feed). • In the webhook node, confirm the URL/path you want external tools or other workflows to call with a “link” field. • Run the manual trigger with one test blog URL to verify: – Article content is extracted correctly. – AI returns LinkedIn/X/Reddit posts and image prompts. – Posts and images appear correctly on all social accounts. • Once tests look good, enable the Schedule Trigger so Blog2Social AI runs automatically at your chosen interval.

This workflow monitors brand mentions across multiple platforms (Twitter/X, Reddit, News) and automatically detects reputation crises based on sentiment analysis and trend detection. How it works Multi-platform monitoring: Every 10 minutes, scans Twitter/X, Reddit, and news sites for brand mentions Data normalization: Converts all platform data into unified format Smart filtering: Removes duplicates and already-analyzed mentions AI sentiment analysis: Analyzes each mention for: Sentiment score (positive/negative/neutral) Amplification factors (engagement, verified accounts, news sources) Crisis-level phrases and keywords Trend detection: Compares current sentiment to 24-hour baseline: Detects sharp sentiment drops Identifies negative mention spikes Calculates impact surge Crisis classification: Assigns severity (CRITICAL/HIGH/MEDIUM/LOW) Automated response: For crises, triggers immediate alerts: Executive crisis brief with action plan Slack alerts to crisis team Email to leadership and PR team JIRA ticket creation Crisis event logging Setup steps Connect platforms: Twitter/X: Add OAuth credentials to "Monitor Twitter/X" node Reddit: Add OAuth credentials to "Monitor Reddit" node News API: Get API key from newsapi.org and add to "Monitor News & Blogs" node Configure brand monitoring: Update brand name and handles in search queries Add additional platforms if needed (LinkedIn, Facebook, Instagram) Set up alerting: Slack: Add credentials and update channel names Email: Add SMTP settings and recipient lists JIRA: Add credentials and project ID Adjust sensitivity: Modify sentiment keyword dictionaries in "AI Sentiment Analysis Engine" Adjust crisis threshold scores Customize amplification factors Test thoroughly: Run manual execution with test data Verify alert routing and content Test false positive handling Activate: Enable for continuous 24/7 monitoring Key Features: Multi-platform monitoring** (every 10 minutes): Twitter/X, Reddit, and News sites Data normalization** that converts different platform formats into unified structure AI sentiment analysis** engine that evaluates: Sentiment keywords (critical, severe, moderate, mild negative/positive) Amplification factors (engagement, verified accounts, follower counts) Impact scoring based on reach and influence Baseline trend detection** that tracks 24-hour sentiment history and detects: Sharp sentiment drops (15+ points = crisis) Negative mention spikes (30%+ increase) Impact surges Automated crisis response workflow**: Aggregates crisis mentions into executive brief Generates detailed action plan based on severity Sends Slack alerts to crisis team Emails leadership with comprehensive brief Creates JIRA ticket for tracking Logs all events for analysis Two-path routing**: Crisis-level events trigger full response workflow, while routine mentions are logged for trend analysis