Automated Multi-Source Content Discovery Workflow

This n8n workflow is designed to automate the process of discovering and aggregating up-to-date information sources across various platforms, including search engines, social media, repositories, and news outlets. It orchestrates multiple data collection methods to find relevant sources based on specific themes or keywords, filter out duplicates or undesired sources, and fetch content or links from these sources for thorough analysis. The workflow begins with scheduled triggers or manual execution, then uses nodes for web searches, social media RSS feeds, and GitHub repositories to gather potential sources. It cleans and filters this data by removing duplicates, irrelevant links, and already known sources. Additional steps include extracting URLs from web content, limiting results to manageable volumes, and utilizing AI language models for relevance assessments. The final outputs are well-organized, relevant, and fresh sources ready for review or integration into further research, content marketing, or competitor analysis. Its flexible structure allows for customized theme targeting and filtering, making it suitable for researchers, journalists, content marketers, and academic resource gatherers who need continuous, automated source discovery.