Master Twitter Data Scraping: Workflow Tutorial by Nate Herk
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In this riveting episode of Nate Herk's AI Automation extravaganza, we dive headfirst into the thrilling world of scraping tweets for market insights, competitor analysis, and staying ahead of the curve in industry trends. Nate unveils a nifty workflow that streamlines the process, making it as easy as pie. The system is a powerhouse, updating a Google sheet with tweet details faster than a Bugatti Veyron on the Autobahn.
With the swagger of a seasoned pro, Nate walks us through setting up the API call step by step, leaving no stone unturned. He breaks down the intricacies of checking counts, setting variables, and navigating pagination like a maestro conducting a symphony. It's a masterclass in efficiency and finesse, all while keeping the audience on the edge of their seats.
As the demo unfolds, Nate delves into the Twitter API pricing, showcasing its affordability and user-friendly pay-as-you-go model. He dishes out insider tips on copying curl commands from API documentation for seamless HTTP requests, making the whole process feel like a walk in the park. Nate's enthusiasm is infectious as he guides us through configuring methods, URLs, and authorizations with the precision of a Formula 1 pit crew.
The adrenaline rush continues as Nate sheds light on the query and query type fields required for advanced search endpoints, demystifying the technical jargon with ease. He touches on the importance of pagination for fetching more tweets and demonstrates testing the API step live, leaving viewers with a newfound sense of empowerment. The episode culminates in a thrilling finale as Nate showcases how to clean up and extract tweet fields using code nodes, a feat that would make even the most seasoned tech enthusiasts nod in approval.
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Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
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