Social Media Sentiment Analyzer Pro
Pricing
from $10.00 / 1,000 results
Social Media Sentiment Analyzer Pro
Advanced sentiment analysis for social media posts. Detects emotions, calculates engagement metrics, extracts hashtags, and identifies trends across platforms.
Pricing
from $10.00 / 1,000 results
Rating
0.0
(0)
Developer

B Butera
Actor stats
0
Bookmarked
6
Total users
2
Monthly active users
10 days ago
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Social Media Sentiment Analyzer
🎯 Overview
The Social Media Sentiment Analyzer is an advanced AI-powered actor that analyzes sentiment, emotions, and engagement metrics from social media posts across multiple platforms including Instagram, Twitter/X, TikTok, LinkedIn, and Facebook.
Perfect for brand monitoring, market research, competitive intelligence, and campaign analysis.
✨ Key Features
Sentiment Analysis
- Three-tier sentiment classification: Positive, Negative, Neutral
- Sentiment scoring: Quantified sentiment values from -1 to 1
- Real-time analysis: Process posts instantly
Emotion Detection
Identifies five primary emotions:
- 😊 Joy - happiness, excitement, enthusiasm
- 😠 Anger - frustration, rage, disappointment
- 😢 Sadness - unhappiness, despair, disappointment
- 😨 Fear - anxiety, worry, concern
- 😲 Surprise - shock, astonishment, amazement
Engagement Metrics
- Engagement Rate: Calculates interaction ratio (likes, comments, shares vs views)
- Virality Index: Measures share-to-like ratio for viral potential
- Total Interactions: Aggregates all engagement types
Content Analysis
- Hashtag Extraction: Identifies and counts hashtags
- User Mentions: Detects @mentions for network analysis
- Keyword Filtering: Filter results by specific keywords or emotions
- Trend Identification: Automatically identifies trending topics
📋 Input Format
{"posts": [{"id": "post_123","platform": "instagram","author": "brandname","content": "Amazing new product launch! #excited #innovation","timestamp": "2025-12-27T19:00:00Z","likes": 1250,"comments": 89,"shares": 42,"views": 15000}],"filterBySentiment": null,"filterByEmotion": null,"minEngagement": 0,"exportFormat": "json"}```### Input Parameters| Parameter | Type | Required | Description ||-----------|------|----------|-------------|| `posts` | Array | Yes | Array of social media post objects || `filterBySentiment` | String | No | Filter by 'positive', 'negative', or 'neutral' || `filterByEmotion` | String | No | Filter by emotion type (joy, anger, sadness, fear, surprise) || `minEngagement` | Number | No | Minimum engagement rate threshold (0-100) || `exportFormat` | String | No | Output format: 'json' or 'csv' (default: 'json') |### Post Object Fields| Field | Type | Required | Description ||-------|------|----------|-------------|| `id` | String | Yes | Unique post identifier || `platform` | String | Yes | Social media platform (instagram, twitter, tiktok, linkedin, facebook) || `author` | String | Yes | Post author/username || `content` | String | Yes | Post text content || `timestamp` | String | No | ISO 8601 timestamp || `likes` | Number | No | Number of likes (default: 0) || `comments` | Number | No | Number of comments (default: 0) || `shares` | Number | No | Number of shares (default: 0) || `views` | Number | No | Number of views/impressions (default: 1) |## 📤 Output Format```json{"results": [{"platform": "instagram","postId": "post_123","author": "brandname","content": "Amazing new product launch! #excited #innovation","timestamp": "2025-12-27T19:00:00Z","sentiment": "positive","sentimentScore": 0.85,"emotions": [{"emotion": "joy","confidence": 0.95},{"emotion": "surprise","confidence": 0.6}],"engagement": {"likes": 1250,"comments": 89,"shares": 42,"views": 15000,"engagementRate": 8.95,"virality Index": 3.36,"totalInteractions": 1381},"hashtags": ["#excited", "#innovation"],"mentionedUsers": [],"analysisTimestamp": "2025-12-27T19:05:00Z"}],"summary": {"totalPostsAnalyzed": 1,"totalPostsMatched": 1,"sentimentDistribution": {"positive": 1,"negative": 0,"neutral": 0},"averageSentimentScore": 0.85,"topEmotions": [{"emotion": "joy","count": 1}],"topHashtags": [{"hashtag": "#excited","count": 1},{"hashtag": "#innovation","count": 1}],"totalEngagement": 1381,"analysisTimestamp": "2025-12-27T19:05:00Z"}}```## 🚀 Quick Start### Basic Usage1. **Prepare your posts data** in the input format above2. **Run the actor** with your posts array3. **Receive analyzed results** with sentiment, emotions, and engagement metrics### Example: Analyze Brand Campaign```json{"posts": [{"id": "post_456","platform": "twitter","author": "YourBrand","content": "Excited to announce our new partnership with TechCorp! This is fantastic news for our users. #partnership #growth","timestamp": "2025-12-27T10:30:00Z","likes": 5432,"comments": 234,"shares": 892,"views": 125000}],"filterBySentiment": "positive","minEngagement": 2}```## 💡 Use Cases### Brand MonitoringMonitor how customers feel about your brand across all platforms- Track sentiment trends over time- Identify negative sentiment spikes- Celebrate viral positive moments### Competitive IntelligenceAnalyze competitor social media sentiment- Compare sentiment across brands- Understand audience perception shifts- Track campaign effectiveness### Campaign AnalysisMeasure sentiment impact of marketing campaigns- Pre/post campaign sentiment comparison- Identify high-performing content themes- Optimize messaging based on emotional response### Market ResearchUnderstand industry sentiment and trends- Track industry sentiment trends- Identify emerging topics and concerns- Monitor influencer sentiment### Customer Feedback AnalysisAnalyze customer reactions to product launches- Detect customer pain points- Identify customer joy moments- Improve product development insights## 🔧 Technical Details### Technology Stack- **Runtime**: Node.js with Apify SDK- **NLP Engine**: Lexicon-based sentiment analysis- **Data Storage**: Apify Dataset format### Performance Characteristics- **Processing Speed**: ~100 posts per second- **Memory Usage**: ~512 MB base- **Timeout**: 60 minutes (adjustable)### Sentiment AlgorithmUses a comprehensive lexicon of positive and negative keywords combined with contextual analysis to determine sentiment polarity and strength.### Emotion DetectionEmploys keyword matching with confidence scoring to identify which of the five emotions are present in the text.## 📊 Output Metrics Explained### Sentiment Score- **Range**: -1.0 to 1.0- **>0.1**: Positive sentiment- **-0.1 to 0.1**: Neutral sentiment- **<-0.1**: Negative sentiment### Engagement RateFormula: `(likes + comments×2 + shares×3) / views × 100`### Virality IndexFormula: `(shares / (likes + 1)) × 100`## 🎓 Examples### Example 1: Product Launch AnalysisAnalyze reactions to a product launch across multiple platforms.### Example 2: Crisis ManagementQuickly identify negative sentiment spikes and affected content.### Example 3: Influencer VettingAnalyze influencer sentiment and audience engagement quality.## 📝 Notes- Sentiment analysis is probabilistic and may not be 100% accurate- Sarcasm and irony may be misclassified- Multiple languages support is planned for future versions- Real-time API streaming coming in v2.0## 🤝 Support & FeedbackNeed help? Have suggestions? Contact our support team or create an issue on GitHub.## 📄 LicenseThis actor is provided under the Apify platform license.## 🔄 Version History### v0.0.1 (Current)- Initial release- Core sentiment analysis- Emotion detection- Engagement metrics- Multi-platform support---**Made with ❤️ for the Apify community**