Social media sentiment analysis dashboard with custom AI for Twitter, Reddit & LinkedIn

Social Media Sentiment Analysis Dashboard with AI and Real-time Monitoring 🎯 Target Audience - Social media managers and community managers - Marketing teams monitoring brand reputation - PR professionals tracking public sentiment - Customer service teams identifying trending issues - Business analysts measuring social media ROI - Brand managers protecting brand reputation - Product managers gathering user feedback 🚀 Problem Statement Manual social media monitoring is overwhelming and often misses critical sentiment shifts or trending topics. This template solves the challenge of automatically collecting, analyzing, and visualizing social media sentiment data across multiple platforms to provide actionable insights for brand management and customer engagement. 🔧 How it Works This workflow automatically monitors social media platforms using AI-powered sentiment analysis, processes mentions and conversations, and provides real-time insights through a comprehensive dashboard. Key Components 1. Scheduled Trigger - Runs the workflow at specified intervals to maintain real-time monitoring 2. AI-Powered Sentiment Analysis - Uses advanced NLP to analyze sentiment, emotions, and topics 3. Multi-Platform Integration - Monitors Twitter, Reddit, and other social platforms 4. Real-time Alerting - Sends notifications for critical sentiment changes or viral content 5. Dashboard Integration - Stores all data in Google Sheets for comprehensive analysis and reporting 📊 Google Sheets Column Specifications The template creates the following columns in your Google Sheets: | Column | Data Type | Description | Example | |--------|-----------|-------------|---------| | timestamp | DateTime | When the mention was recorded | "2024-01-15T10:30:00Z" | | platform | String | Social media platform | "Twitter" | | username | String | User who posted the content | "@johndoe" | | content | String | Full text of the post/comment | "Love the new product features!" | | sentimentscore | Number | Sentiment score (-1 to 1) | 0.85 | | sentimentlabel | String | Sentiment classification | "Positive" | | emotion | String | Primary emotion detected | "Joy" | | topics | Array | Key topics identified | "product", "features" | | engagement | Number | Likes, shares, comments | 1250 | | reachestimate | Number | Estimated reach | 50000 | | influencescore | Number | User influence metric | 0.75 | | alertpriority | String | Alert priority level | "High" | 🛠️ Setup Instructions Estimated setup time: 20-25 minutes Prerequisites - n8n instance with community nodes enabled - ScrapeGraphAI API account and credentials - Google Sheets account with API access - Slack workspace for notifications (optional) - Social media API access (Twitter, Reddit, etc.) Step-by-Step Configuration 1. Install Community Nodes bash Install required community nodes npm install n8n-nodes-scrapegraphai npm install n8n-nodes-slack 2. Configure ScrapeGraphAI Credentials - Navigate to Credentials in your n8n instance - Add new ScrapeGraphAI API credentials - Enter your API key from ScrapeGraphAI dashboard - Test the connection to ensure it's working 3. Set up Google Sheets Connection - Add Google Sheets OAuth2 credentials - Grant necessary permissions for spreadsheet access - Create a new spreadsheet for sentiment analysis data - Configure the sheet name (default: "Sentiment Analysis") 4. Configure Social Media Monitoring - Update the websiteUrl parameters in ScrapeGraphAI nodes - Add URLs for social media platforms you want to monitor - Customize the user prompt to extract specific sentiment data - Set up keywords, hashtags, and brand mentions to track 5. Set up Notification Channels - Configure Slack webhook or API credentials - Set up email service credentials for alerts - Define sentiment thresholds for different alert levels - Test notification delivery 6. Configure Schedule Trigger - Set monitoring frequency (every 15 minutes, hourly, etc.) - Choose appropriate time zones for your business hours - Con