Automate Twitter Sentiment Analysis and Store in Strapi

Overview

This n8n workflow automates the process of gathering tweets, analyzing their sentiment, and storing valuable information in a Strapi CMS. It's designed to capture public opinion on specific topics from Twitter and make it accessible within a structured content management system.

Key Problem Solved: Manually sifting through Twitter data for sentiment analysis is time-consuming and inefficient. This workflow automates that process, allowing you to identify trending opinions and relevant discussions automatically. It also provides a pathway to ingest data from other sources (like form submissions) and analyze them for sentiment.

Workflow Logic:

1. Trigger: The workflow can be triggered either on a schedule (every 30 minutes) or via a webhook for real-time data ingestion.
2. Data Fetching: It searches for recent tweets related to 'strapi' or 'n8n.io' using the Twitter node. If triggered by a webhook, it processes form submission data.
3. Data Simplification: The Simplify Result (for tweets) and Simplify Webhook Result (for form data) nodes extract and reformat relevant fields like content, author, and creation date.
4. Sentiment Analysis: The Analyze Tweet and Analyze Form Submission nodes utilize Google Cloud Natural Language to determine the sentiment score and magnitude of the extracted content.
5. Filtering: Is Retweet or Old? node filters out retweets or tweets older than 30 minutes. Positive Form Sentiment? and Positive Tweet Sentiment? nodes further filter based on sentiment scores.
6. Data Storage: Positive tweets and form submissions are then stored in Strapi using the Store in Strapi node.
7. Merging: Merge Tweet Sentiment with Source and Merge Form Sentiment with Source nodes combine the sentiment analysis results with the original tweet or form data.