Build a Sentiment Dataset by Date Range
Builds a topic dataset from X (Twitter) for sentiment analysis. Set This_exact_phrase (here 'customer service') and a start/end date, and the scraper collects matching tweets day by day with 55 fields each: fullText, language, engagement, author stats and timestamps. Feed the text and metrics into sentiment and NLP pipelines. Export to CSV or JSON.
Input
Output fields
Sign up on Apify or log in
The Twitter Advanced Search Scraper - Export X Tweets & Media Actor is ready to run with the inputs already set for "Build a Sentiment Dataset by Date Range". Sign up or log in and you'll land in Apify Console with a copy of this exact task.
Start the "Build a Sentiment Dataset by Date Range" task
The Twitter Advanced Search Scraper - Export X Tweets & Media Actor will start running based on the input automatically. You can also change all the input fields, like this exact phrase, start date (optional), and more, to match your specific use case.
Receive the "Build a Sentiment Dataset by Date Range" output
Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as tweet url, created at, author handle, and more.
Integrate into your workflow
The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Build a Sentiment Dataset by Date Range" task via API.
