Content items and associated criteria for delivery are received by a server from content provider. The server provides online services such as social networking, media hosting and sharing websites, news, etc. The server extracts content features from the content items using text extraction, image processing and other techniques. The server determines a content emotion associated with the content by applying trained machine-learning models. The server selects content items based on the content emotion, detected user emotion of a requesting user, and the criteria associated with different content items. Selected content items are delivered to a requesting user in a ranked order. The server obtains user interaction data from interaction of the requesting user with the delivered content items and detects a user emotion based on the interaction data. The content emotion associated with the content item is adjusted based on an aggregate of the detected emotion of users that received the content item. The adjusted content emotion is used for evaluation of the content item to other users. The described techniques for selection and delivery of content items based on content emotion, and adjustment of the content emotion based on user interaction allow the server to deliver content items that have a high likelihood of providing a quality user experience. The described techniques improve engagement of the user with the online service provided by the server.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.