Facebook, Inc.

Dean Griffin Eckles

Cameron Marlow

Lars Seren Backstrom

Michael Benjamin Nowak

Brian Christopher Karrer

Johan Ugander

Jon Kleinberg

Cameron Alexander Marlow

Gregory Matthew Marra

Mahmud Sami Tas

Vibhi Kant

Yaroslav O Dudin

Systems, methods, and non-transitory computer-readable media can obtain at least one content item to be scored with respect to a user, wherein the score is used to determine whether the content item is included in a content feed of the user. A value for a first event is determined based at least in part on a likelihood of the user performing an action with respect to the content item, wherein the likelihood of the user performing the action is greater than an average user of the social networking system. The score for the content item is determined based at least in part on the value for the first event, wherein the first value is dampened to reduce its contribution to the score.

Systems and methods for content presentation

In one embodiment, a method includes sending, from an application server to a first set of client systems, instructions for providing a treatment to a first set of users. The method includes determining an average treatment effect of the treatment for the first set of users based on information about user interactions associated with the treatment and a network exposure to the treatment for each user. Network exposure for a user is a measure of other users associated with the user that have been provided the treatment. The method includes modifying the treatment based on the determined average treatment effect. The method includes sending, to a second set of client systems, instructions for providing the modified treatment to a second set of users. The second set of users is a discrete, non-overlapping set of users with respect to the first set.

Network-aware product rollout in online social networks

In one embodiment, a method includes accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each node corresponding to a user of an online social network, identifying a plurality of clusters in the social graph using graph clustering, providing a treatment to a first set of users based on the clusters, and determining a treatment effect treatment for the users in the first set based on a network exposure to the treatment for each user.

Network aware product rollout in online social networks

A social networking system obtains linguistic data from a user's text communications on the social networking system. For example, occurrences of words in various types of communications by the user in the social networking system are determined. The linguistic data and non-linguistic data associated with the user are used in a trained model to predict one or more personality characteristics for the user. The inferred personality characteristics are stored in connection with the user's profile, and may be used for targeting, ranking, selecting versions of products, and various other purposes.

Determining user personality characteristics from social networking system communications and characteristics

Growing community of inventors

San Francisco, CA, United States of America

Dean Griffin Eckles