9. A system comprising: one or more processors; and one or more memories storing instructions that, when executed, cause the system to: retrieve social network data associated with a user; extract one or more of a keyword and a key phrase from the social network data; determine a preference model that includes a frequency analysis associated with the one or more of the keyword and the key phrase, the frequency analysis indicating how often the one or more of the keyword and the key phrase are observed in the social network data; receive a request for content data; search a content database to retrieve one or more content items based on the frequency analysis associated with the preference model; generate one or more recommended items for the user or for a vehicle system from the one or more content items; and provide the one or more recommended items for presentation to the user or for processing by the vehicle system.
9. A system comprising: one or more processors; and one or more memories storing instructions that, when executed, cause the system to: retrieve social network data associated with a user; extract one or more of a keyword and a key phrase from the social network data; determine a preference model that includes a frequency analysis associated with the one or more of the keyword and the key phrase, the frequency analysis indicating how often the one or more of the keyword and the key phrase are observed in the social network data; receive a request for content data; search a content database to retrieve one or more content items based on the frequency analysis associated with the preference model; generate one or more recommended items for the user or for a vehicle system from the one or more content items; and provide the one or more recommended items for presentation to the user or for processing by the vehicle system. 15. The system of claim 9 , wherein the instructions when executed cause the system to also: receive feedback data describing one or more user interactions with the one or more recommended items; and refine the preference model based on the feedback data.