The Twitter Recommendation Algorithm is a set of services and jobs that are responsible for constructing and serving the Home Timeline. This algorithm includes several main components such as SimClusters, TwHIN, trust-and-safety-models, real-graph, tweepcred, recos-injector, and graph-feature-service. Moreover, there are several candidate sources like search-index, cr-mixer, user-tweet-entity-graph (UTEG), and follow-recommendation-service (FRS), as well as ranking services such as light-ranker and heavy-ranker. Finally, there are tweet mixing and filtering services like home-mixer and visibility-filters. All these components work together to provide users with the most relevant and personalized content on their home timeline.
