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Tutorials intermediate Elena Torres ·

AI Social Media Monitoring 2026: Build a Real-Time Listening Dashboard

AI Social Media Monitoring 2026: Build a Real-Time Listening Dashboard

What You’ll Build

A real-time social media monitoring dashboard powered by AI that tracks brand mentions, analyzes sentiment, identifies trending topics, and sends daily briefs — all without expensive enterprise tools. You’ll connect multiple data sources (Reddit, Twitter/X, news RSS) through n8n and use LLMs for intelligent analysis.

Prerequisites

  • n8n account (self-hosted or cloud, free tier works)
  • OpenAI API key or Claude API key
  • Basic knowledge of JSON and webhooks
  • Optional: Twitter API v2 access (free tier available)
  • A Google Sheets account (for the dashboard data store)

Step 1: Set Up Your Data Sources

The best monitoring covers multiple channels. Start with three free, high-signal sources.

Reddit Monitoring

Reddit is the best free source for unfiltered brand conversation. Use n8n’s built-in Reddit node:

  1. Create a new n8n workflow
  2. Add a Schedule Trigger (every 30 minutes)
  3. Add a Reddit node configured to search:
    • Subreddit: all (or specific niche subreddits)
    • Query: "your brand name" OR "your product"
    • Sort: new
    • Limit: 25
  4. Add a Code node to filter duplicates (use a simple dedup cache)

Twitter/X Monitoring

Even the free Twitter API v2 tier gives you filtered stream access:

# Set up a filtered stream rule via cURL
curl -X POST -H "Authorization: Bearer $BEARER_TOKEN" \
  -H "Content-Type: application/json" \
  "https://api.twitter.com/2/tweets/search/stream/rules" \
  -d '{"add": [{"value": "yourbrand -is:retweet lang:en", "tag": "brand mentions"}]}'

Connect the stream to n8n via webhook using the Twitter API node.

RSS News Feeds

Don’t ignore traditional media. Add RSS sources:

- Google News RSS: https://news.google.com/rss/search?q=your+brand
- TechCrunch: https://techcrunch.com/feed/
- Industry-specific blogs

Use n8n’s RSS Feed Read node to poll these every 60 minutes.

Step 2: Build the AI Analysis Pipeline

Raw mentions are noise. The AI layer turns them into intelligence.

Sentiment Analysis

Add an OpenAI node after your data sources with this prompt:

Analyze the sentiment of the following social media mention.
Return JSON with these fields:
- sentiment: "positive" | "negative" | "neutral" | "mixed"
- score: number from -1.0 to 1.0
- key_topics: array of main topics mentioned
- urgency: "low" | "medium" | "high" (high = needs immediate response)
- summary: one-sentence summary

Mention: "{{ $json.text }}"

Topic Clustering

Add a second analysis step to cluster mentions into themes:

Cluster these mentions into 3-5 major themes.
For each theme, provide:
- theme_name
- mention_count
- representative_quotes (top 2-3)
- overall_sentiment

Mentions: [{{ $json.mentions }}]

Store results in a Google Sheets row with columns: timestamp | source | text | sentiment | score | topics | urgency | theme

Step 3: Build the Alert System

Not all mentions are equal. Build smart alerts for what matters.

Urgency Detection

Create a conditional routing node in n8n:

// Code node: urgency routing
const urgency = $input.first().json.urgency;
const sentiment = $input.first().json.sentiment;

if (urgency === "high" && sentiment === "negative") {
  // Route to Slack ASAP
  return { action: "alert_immediate" };
} else if (urgency === "high") {
  // Route to email digest
  return { action: "alert_daily" };
} else {
  // Log to analytics sheet
  return { action: "log_only" };
}

Slack Integration

For high-urgency mentions, send a formatted Slack alert:

🚨 *URGENT MENTION DETECTED*
*Source:* {{ $json.source }}
*Sentiment:* {{ $json.sentiment }}
*Text:* {{ $json.text }}
*URL:* {{ $json.url }}
*Key Topics:* {{ $json.key_topics }}

Daily Digest Email

For lower priority, build a daily summary email using HTML:

<h2>Daily Social Listening Brief — {{date}}</h2>
<p>Total mentions: {{total}}</p>
<p>Sentiment breakdown: 👍 {{positive}} | 👎 {{negative}} | 😐 {{neutral}}</p>
<h3>Top Themes</h3>
<ul>
{{#each themes}}
  <li><strong>{{theme_name}}</strong>: {{mention_count}} mentions</li>
{{/each}}
</ul>

Step 4: Visualization Dashboard

Turn your Google Sheets data into a live dashboard.

Option A: Google Looker Studio (Free)

  1. Connect Google Sheets to Looker Studio
  2. Create charts:
    • Time series: Mentions over time (line chart)
    • Sentiment breakdown (pie chart)
    • Top topics (bar chart)
    • Source distribution (donut chart)
  3. Set auto-refresh: 15 minutes

Option B: Grafana + n8n

For a more technical setup, push metrics to Grafana via Prometheus:

# n8n HTTP Request node to push to Prometheus pushgateway
URL: http://your-grafana:9091/metrics/job/social_monitoring
Method: POST
Body: social_mentions_total{source="reddit"} 42

Step 5: Weekly Trend Report

Go beyond daily monitoring with weekly trend analysis.

Analyze this week's social mentions data:
[Paste raw data from Google Sheets]

Generate a structured report:
1. Weekly sentiment trend (improved/declined/stable)
2. Top 5 mentioned topics and their sentiment
3. Emerging trends (topics growing faster than others)
4. Competitor comparison if competitor mentions are tagged
5. Recommendations for next week's content strategy

Format as HTML suitable for email.

Schedule this as a weekly n8n workflow using the Schedule Trigger (Monday at 9 AM).

Troubleshooting

IssueSolution
Twitter API rate limitsUse 2-minute polling intervals and cache results
Reddit API returns emptyCheck subreddit spelling and ensure query isn’t too restrictive
Sentiment analysis is wrongAdd brand-specific context in the prompt (e.g., “our product is a SaaS tool”)
Too many false positivesAdd keyword exclusions — filter out job postings and spam
Google Sheets too slowSwitch to a database like Supabase (free tier) for production use
Missing important sourcesExpand to YouTube comments, Discord, and product review sites

Next Steps

  1. Set up your n8n workflow with Reddit and RSS feeds first (easiest to test)
  2. Add Twitter/X monitoring once the pipeline is working
  3. Configure the Slack alert system for real-time notifications
  4. Build the Looker Studio dashboard for weekly reviews
  5. Share the daily digest with your team

Advanced: Add competitor tracking by duplicating the workflow with competitor brand names. Use LLM analysis to compare brand sentiment side-by-side and identify competitive advantages or vulnerabilities.