Monitor brand mentions with OpenAI across Twitter/X, Reddit, News, Airtable and Slack

Monitors brand mentions across Twitter/X, Reddit, and News APIs in real-time (or scheduled), fetches mentions in parallel, normalizes data, uses AI to analyze sentiment/urgency/topics, detects duplicates, filters critical mentions, logs everything to Airtable, posts alerts to Slack, and emails daily HTML digest reports to the marketing team.

Good to Know

• Runs every hour (configurable) to provide near-real-time brand monitoring
• Pulls mentions from multiple platforms in parallel: Twitter/X, Reddit, News sources
• Uses AI (OpenAI/Grok/etc.) for advanced sentiment classification, urgency detection, topic extraction, and duplicate deduplication
• Focuses on actionable insights: flags negative/urgent mentions for immediate response
• Generates beautiful HTML daily digest with summarized mentions, sentiment trends, and key highlights
• Stores historical data in Airtable for tracking, analytics, and long-term reporting
• Sends real-time Slack alerts for high-priority/negative mentions
• Reduces manual social monitoring time dramatically and helps catch reputation issues early

How It Works

1. Trigger & configure

• Schedule Trigger — Runs every hour (or custom interval) to check for new brand mentions
• Set brand monitoring config — Defines brand name, keywords, excluded terms, monitoring parameters (via Set node or variables)

2. Fetch & collect mentions

• Fetch Twitter/X mentions — Uses Twitter/X node or HTTP Request to search recent tweets (mentions, keywords)
• Fetch Reddit mentions — Searches relevant subreddits or Reddit-wide for brand keywords/posts
• Fetch news article mentions — Queries news APIs (e.g. NewsAPI, Google News via RSS/HTTP) for brand coverage
• Merge platform mentions — Combines results from all sources into a unified stream
• Normalize mentions into unified schema — Standardizes fields (text, author, platform, timestamp, URL, etc.) for consistent processing

3. AI analyze & deduplicate

• AI sentiment and urgency analysis — Sends mentions to AI model (OpenAI node) with prompt to classify:
• Sentiment: positive / neutral / negative
• Urgency/severity: low / medium / high / critical
• Topics/themes
• Key excerpts
• Wait For Result — Ensures AI responses are complete
• Process analysis results — Parses structured JSON output from AI
• Filter mentions requiring alerts — Routes based on sentiment/urgency thresholds
• Deduplicate — Removes near-duplicate mentions (e.g. same content reposted)

4. Store, alert & report

• Log mention to Airtable — Appends/updates records with full details, sentiment, AI analysis, timestamp
• Route by sentiment and urgency — Critical/negative → immediate action path
• Send mention alert — Posts formatted message to Slack (or Discord/Teams) with link, text snippet, sentiment badge
• Generate HTML daily digest report — Compiles summary: total mentions, sentiment breakdown, top issues, trends
• Email HTML digest — Sends polished report to marketing team via Email node (SMTP/Gmail)
• Log success and update listings — Records workflow completion, stats for monitoring

Data Sources

• Twitter/X — Recent search for mentions/keywords (via Twitter node or HTTP Request with API)
• Reddit — Subreddit or site-wide search for brand mentions
• News APIs — NewsAPI.org, Google News RSS, or similar for article mentions
• AI Model — OpenAI (GPT-4o / GPT series), Grok, or other LLM for sentiment/urgency analysis
• Storage — Airtable base (tables for mentions, daily summaries)
• Notifications — Slack (webhook or app), Email (SMTP)

How to Use

1. Import the workflow JSON into your n8n instance
2. Configure credentials:

• Twitter/X API (OAuth or Bearer token for search)
• Reddit API (if using official; or RSS/HTTP for subreddits)
• News API key (e.g. NewsAPI.org)
• OpenAI API key (or Grok/other LLM)
• Airtable API key + base/table
• Slack webhook or app token
• Email SMTP credentials

1. Set monitoring parameters — Edit brand name, keywords, exclude lists in Set monitoring config node
2. Customize AI prompt — In the AI sentiment node, tweak for brand-specific tone, industry terms, urgency criteria
3. Adjust schedule — Change interval in Monitor mentions every hour trigger
4. Tune filters — Set thresholds for alerts (e.g. only negative + high urgency)
5. Test manually — Use Execute Workflow to simulate with known mentions
6. Activate — Turn on and watch Executions + Airtable/Slack for results

Requirements

• n8n instance (self-hosted or cloud)
• API access/keys for Twitter/X, Reddit (optional), News source
• OpenAI (or compatible LLM) API key with good token limit
• Airtable workspace/base for logging
• Slack workspace for alerts
• Email account for daily digests

Customizing This Workflow

• Add more platforms — Include Facebook/Instagram (via Meta API), LinkedIn, Discord mentions
• Enhance AI analysis — Add topic clustering, competitor comparison, virality scoring
• Improve deduplication — Use fuzzy matching or embeddings for better duplicate detection
• Visual dashboard — Export Airtable data to Google Looker Studio / Grafana for sentiment trends
• Auto-response — For low-risk positive mentions, generate draft replies
• Language support — Add multilingual sentiment detection
• Hourly vs. real-time — Switch to webhook triggers if platforms support (e.g. Twitter webhooks if available)
• Daily/weekly reports — Aggregate more stats, charts in HTML email