Filtering Instagram Hashtags Using Crowd Tagging and HITS Algorithm

This project optimizes Instagram hashtag filtering by combining community tagging with the Hyperlink-Induced Topic Search (HITS) algorithm. The HITS algorithm examines the many user inputs gathered via crowd tagging to determine the significance of hashtags, with a particular emphasis on authority and hub ratings. This technique enhances Instagram content quality and discovery by removing offensive and deceptive hashtags. The method is scalable, allowing for real-time hashtag analysis and filtering to uphold community norms. This could serve applications in content management across social media platforms.