How the AI Works

1. Data Collection and Monitoring

   • The system continuously monitors platforms like Twitter, scanning for posts in real time using APIs.

   • Keywords, hashtags, and trending topics commonly associated with "woke" content are used to filter posts for analysis.

2. Content Analysis with NLP

   • The AI employs Natural Language Processing (NLP) to evaluate the text, identifying specific linguistic patterns and themes that align with "woke" ideology.

   • Key indicators include:

     • Overuse of buzzwords (e.g., "privilege," "systemic," "equity").

     • Phrasing that aligns with social justice activism.

     • High emotional tone tied to divisive social issues.

3. Scoring Mechanism

   • Each post is scored based on its "wokeness" using a proprietary algorithm.

   • The algorithm considers:

     • Frequency of flagged terms.

     • Contextual relevance to woke topics.

     • Sentiment analysis, focusing on exaggerated moral or ideological positioning.

4. Threshold and Classification

   • If a post's score exceeds the predefined "woke threshold," it is classified as "woke" and flagged for action.

   • Posts with borderline scores are stored for further review to improve model accuracy.

5. Automated Retweet with "Woke Mark"

   • Once flagged, the AI automatically retweets the post with a "Woke Mark," such as:

     • A warning text: “⚠️ Woke Alert: This post has been flagged for ideological content. Proceed with caution.”

     • Specific hashtags like #WokeMark or #NotBased.

     • A predefined reply that adds a humorous or critical comment.