Facebook, Inc.

Jonathan J Gross

Eugene Zarakhovsky

Yihua Liao

Joshua Luke Krivoshein

Monika Leigh Bickert

Jason Duane Clark

Vijaye Ganesh Raji

Brent Dorman

Embodiments are disclosed for identifying a suspect application based on multiple operating factors from use of multiple applications. The embodiments can generate a representative distribution of a selected factor based on collected information corresponding to multiple operating factors from use of multiple applications. The embodiments can compare a representative distribution of a target factor with the representative distribution of the selected factor and identify a suspect application when these distributions are different.

Detecting fraud in connection with adverstisements

An online system extracts features from an application linked to the online system. The application is used by users of the online system and posts content to the online system. A trained model is applied to the extracted features to generate a quality score for the application. The trained model is trained using features extracted from a set of training applications and quality scores manually assigned to the training applications, wherein the manually assigned quality scores indicate whether each training application satisfies a set of criteria and the generated quality score represents a probability of the application satisfying the set of criteria. Based on the quality score, content provided by the application is ranked for presentation to a user of the online system in relation to other content of the online system. The online system presents the content provided by the application to the user according to the ranking.

Analyzing quality of applications linked to an online system

Growing community of inventors

Seattle, WA, United States of America

Jonathan J Gross