Behavioral Analysis

Companion AI employs a two-stage processing pipeline to create a behavioral blueprint:

1. Tone and Style Analysis:

   • Uses NLP models to extract linguistic features (e.g., formality, humor, sarcasm).

   • Identifies recurring patterns (e.g., emoji usage, slang, hashtags).

2. Content Preference Analysis:

   • Categorizes topics using topic modeling (e.g., Latent Dirichlet Allocation).

   • Analyzes engagement metrics to prioritize high-performing content types (e.g., threads vs. single tweets).

Tech Stack:

• Transformers (Hugging Face): For sentiment analysis and tone detection (e.g., BERT-based models).

• SpaCy: For entity recognition and linguistic feature extraction.

• Grok 3 (xAI): For advanced NLP tasks, leveraging its contextual understanding (via xAI API).

• PostgreSQL: For storing behavioral blueprints and metadata.