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
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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
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Configure brand monitoring:
- Update brand name and handles in search queries
- Add additional platforms if needed (LinkedIn, Facebook, Instagram)
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Set up alerting:
- Slack: Add credentials and update channel names
- Email: Add SMTP settings and recipient lists
- JIRA: Add credentials and project ID
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Adjust sensitivity:
- Modify sentiment keyword dictionaries in "AI Sentiment Analysis Engine"
- Adjust crisis threshold scores
- Customize amplification factors
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Test thoroughly:
- Run manual execution with test data
- Verify alert routing and content
- Test false positive handling
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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