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Twitter Plugin Timeline Flow - Detailed Breakdown

This document provides a comprehensive breakdown of how the Twitter plugin processes timeline data and generates interactions.

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Complete Timeline Flow Diagram

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Detailed Processing Flows

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1. Timeline Fetching

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2. Weighted Algorithm Flow

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3. Interaction Decision Flow

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4. Response Generation Flow

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5. Action Processing Flow

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Timeline State Management

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Cache Structure

interface TimelineCache {
  tweets: Tweet[];
  users: Map<string, TwitterUser>;
  timestamp: number;
  etag?: string;
}

interface ProcessingState {
  processedTweets: Set<string>;
  lastProcessTime: number;
  interactionCount: number;
  rateLimitStatus: RateLimitInfo;
}

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Scoring Components

interface ScoringWeights {
  user: number;      // Default: 3
  time: number;      // Default: 2
  relevance: number; // Default: 5
}

interface TweetScore {
  tweetId: string;
  userScore: number;
  timeScore: number;
  relevanceScore: number;
  totalScore: number;
  factors: {
    isTargetUser: boolean;
    isVerified: boolean;
    followerCount: number;
    hasKeywords: boolean;
    age: number;
  };
}

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Error Handling in Timeline Flow

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Performance Optimization

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Batch Processing

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Processing Pipeline

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Monitoring & Metrics

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Timeline Processing Metrics

interface TimelineMetrics {
  fetchTime: number;
  tweetCount: number;
  newTweetCount: number;
  processedCount: number;
  interactionCount: number;
  errorCount: number;
  cacheHitRate: number;
  averageScore: number;
}

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Performance Tracking

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Configuration Impact

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Algorithm Selection

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Weight Configuration Effects

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Best Practices

1. Cache Management

   • Implement TTL for timeline cache
   • Clear processed tweets periodically
   • Monitor cache hit rates

2. Rate Limit Handling

   • Track limits per endpoint
   • Implement request queuing
   • Use exponential backoff

3. Score Tuning

   • Monitor interaction quality
   • Adjust weights based on results
   • A/B test different configurations

4. Error Recovery

   • Implement circuit breakers
   • Log all failures with context
   • Graceful degradation

5. Performance Monitoring

   • Track processing times
   • Monitor API usage
   • Alert on anomalies