How X-Score AI Works
Learn how X-score uses artificial intelligence to analyze tweets, detect sentiment, and calculate engagement, reputation, and behavioral scores.
Our Systematic Approach
Our AI-powered analysis follows a rigorous process to deliver accurate insights
Collecting Tweets
Continuous fetching from X API based on mentions and hashtags.
Keyword Detection
Detects mentions, hashtags, and branded terms across multiple languages.
Time Filtering
Define the exact period to analyze — hourly, daily, or custom windows.
Enrichment
Every tweet is enriched with user data like influence score and verification.
Analysis Output Structure
Understanding the detailed metrics returned by X-score AI analysis. Each score is normalized between 0.0 and 1.0.
Alignment
stringClassification of tweet context (positive, neutral, negative, offtopic).
Textual Score
float 0.0-1.0AI assessment of content positivity, informativeness, and relevance.
Engagement Score
float 0.0-1.0Measure considering likes, reposts, replies, and view counts.
Reputation Score
float 0.0-1.0Author authority based on followers, verification, and history.
Behavior Score
float 0.0-1.0User patterns - toxicity, aggression, or promotional frequency.
Final Score
float 0.0-1.0Integrated rating calculated as weighted average of all metrics.
Score Visualization
Input Data
{
"tweets": [
{
"text": "our shop is the best!",
"likeCount": 10,
"replyCount": 2,
"lang": "en",
"author": {
"userName": "test_user",
"followers": 1000,
"isVerified": false
}
}
],
"target_narrative": "analyze best review"
}