Twitter Following Analytics

What Is This About?

A basic analysis that tracks the quality of your Twitter followings and the return on engagement (ROE) for different accounts. This guide shows you how to analyze your Twitter network to understand:

• Influence Map: Visualize your followings by engagement metrics (posts per day, follower ratio)
• Return on Engagement (ROE): Measure which accounts give you the best engagement when you reply to them
• Network Quality: Identify high-value connections in your Twitter network

The Challenge: Understanding Twitter Network Value

Twitter networks are complex:

• Follower Count: Doesn't tell the whole story about account quality
• Engagement Patterns: Some accounts have high follower counts but low engagement
• ROI of Engagement: Not all replies are equal - some accounts provide better returns

This analysis helps you understand which accounts in your network are most valuable for engagement.

Who Is This For?

This guide is designed for:

• Content Creators: Understanding which accounts to engage with for maximum ROI
• Social Media Managers: Analyzing Twitter network quality and engagement patterns
• Data Analysts: Learning how to analyze social media data and create visualizations
• Twitter Power Users: Understanding your network and optimizing engagement strategies
• Anyone Learning Data Analysis: Practical example of API integration, data processing, and visualization

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Generated Results

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Engagement rankings

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How to Do This Properly on Your Own

Code for nerds

Influence map

Engagements

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Has This Helped You?

If you found this Twitter analytics guide useful:

• Share it with your network or on social media
• Bookmark this page for future reference
• Write backlinks to this page when referencing Twitter data analysis

This guide provides a complete reference for:

• Twitter API integration and pagination
• Data caching strategies
• Feature engineering for social media data
• Network visualization
• Engagement ROI analysis

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For Those Who Want to Do It Properly Themselves

1. API Integration: Use Twitter/X API to fetch followings, followers, and tweets
2. Data Processing: Normalize JSON data, engineer features (follow ratio, posts per day)
3. Caching Strategy: Implement caching to reduce API costs and improve performance
4. Visualization: Create scatter plots for influence maps, bar charts for engagement rankings
5. Engagement Analysis: Calculate ROI metrics (views, likes, retweets per reply)

You can adapt the code examples above to:

• Fetch your own Twitter data
• Calculate custom engagement metrics
• Create visualizations tailored to your needs
• Build automated analysis pipelines

Note: Twitter API access requires authentication. Make sure you have valid API keys and understand rate limits.