trigger-chains Scenario 4 — Scrape Social Posts → AI Sentiment → Database → Alert
Written by RTILA X Engineering Team
What You'll Learn
Handle errors across trigger chains
Real-World Use Case
Ensuring data integrity in multi-step pipelines
Social Post Sentiment
Extract posts and sentiment labels for the AI analysis trigger chain.
Sentiment Analysis Pipeline
Positive: 3
Negative: 2
Neutral: 1
Sentiment Summary
{
"positive": 3,
"negative": 2,
"neutral": 1
} RTILA X Automation Project
{
"name": "Scrape_Social_Posts",
"settings": {
"urls": [
"https://learn.rtila.com/scenarios/trigger-chains/4"
]
},
"datasets": {
"social_posts": {
"item_selector": "css=.sentiment-post",
"properties": [
{
"name": "post_text",
"type": "text",
"selector": "css=.post-text"
},
{
"name": "sentiment",
"type": "attribute",
"selector": "css=.sentiment-label",
"attribute": "data-sentiment"
}
]
}
}
} Trigger Chain Configuration
- ai_completion — classifies each post as positive, negative, or neutral.
- database_insert — saves the classified posts to a database.
- alert — sends an alert when negative posts are detected.
Trigger chains are configured in the RTILA X UI, not via project JSON. The AI assistant can discuss them but cannot generate trigger chain configurations.
AI sentiment analysis transforms raw social text into structured categories. A trigger chain can store the analysis and notify teams when negative sentiment appears.
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Ready to run this automation?
Copy the project JSON above, open RTILA X, create a new project, and paste it.
This scenario covers 2 RTILA X commands and is referenced in 2 learning articles.
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