Facebook, Inc.

Meta Platforms, Inc.

Lada Ariana Adamic

Peter Henry Martinazzi

Ariel Benjamin Evnine

Ojus Abhimanyu Patil

Balamanohar Paluri

Yuval Kesten

Erich James Owens

Hermes Germi Pique Corchs

Bogdan State

Mark Andrew Rich

Russell Lee-Goldman

Adrien Thomas Friggeri

Jeffrey C Wieland

Brett Alden Lavalla

Amy Campbell

Nidhi Gupta

Shaomei Wu

Matt King

David M Goldblatt

Andrew Rocco Tresolini Fiore

Omid Farivar

The present disclosure relates to systems and methods for increasing messaging activity in a messaging system. Using the interactions of users with each other and/or with the messaging system, the disclosed systems and methods can predict how likely a pairing of two or more users are to engage in a highly active messaging thread. Based on this prediction, the disclosed methods and systems can, for example, more effectively organize contact lists and conduct promotional efforts associated with messaging features.

Predicting and facilitating increased use of a messaging application

Systems, methods, and non-transitory computer-readable media can receive an image. One or more concepts depicted in the image are identified based on machine learning techniques. The one or more concepts are filtered based on filtering criteria to identify one or more selected concepts. An image description is generated comprising the one or more selected concepts.

Systems and methods for image description generation

Some embodiments include a method of detecting and analyzing virally propagating subject matter in a social networking system. The method includes processing user activities in the social networking system through a relevancy filter to identify a subset of user activities that are relevant to a viral propagation study. The social networking system can construct, in response to selecting a user activity as a graph exploration seed, a user activity cascade by exploring the social graph in the social networking system, starting from a social network node corresponding to the user activity. The user activity cascade can comprise social network nodes found during the graph exploration. The social networking system can determine that the user activity cascade is virally propagating based at least upon a total size of the user activity cascade.

Viral content propagation analyzer in a social networking system

In one embodiment, a method includes receiving unstructured text from a user of a social-networking system, determining whether the unstructured text includes a request for a recommendation, identifying one or more first entity names in the unstructured text, generating a structured query based upon the one or more first entity names, identifying, in the social graph, one or more second entity names corresponding to the structured query, and presenting the one or more second entity names and the unstructured text in a social context of the user. The unstructured text may include text of a post or message generated by the user on a social-networking system. A score may be generated based on the unstructured text to determine whether the text includes a request for recommendation using a machine-learning model based on comparison of the unstructured text to the one or more predetermined words associated with requests for recommendation.

Identifying and processing recommendation requests

Growing community of inventors

Mountain View, CA, United States of America

Lada Ariana Adamic