Porovnání Mastodon API a web scrapingu při získávání veřejně dostupných dat

This bachelor’s thesis compares two approaches to extracting publicly available data from the Mastodon social platform: the API approach and the web scraping approach. The theoretical section presents the basic principles of both approaches, their technical aspects, and the characteristics of the Mastodon platform. The practical section focuses on the implementation and testing of both approaches across three predefined data collection scenarios. Both approaches are evaluated using predefined metrics, including processing time, CPU usage, RAM consumption, record retrieval success rate, attribute completeness, and processing time stability. The thesis concludes with a comparison of both approaches based on the conducted experiments, an interpretation of the obtained results, and an assessment of their suitability for practical use.