Twitter, Inc.

Kelly Huffman

Wook Jin Chung

Kiryl Lashuk

According to an implementation, a method for digital information retrieval in a social media platform includes transmitting, over a network, information to render a timeline of social content for a user of a client application. The timeline of social content includes messages posted on the messaging platform by user accounts that are connected to a user account of the user in a connection graph. The method includes computing, using a machine-learning algorithm inputted with relevance signals, a relevance level between the user account of the user and a user account not linked to the user account of the user in the connection graph, and transmitting information about a profile of the user to a computing device associated with the user account not linked to the user account of the user in response to the relevance level being greater than a threshold level.

Increasing social media presence using machine-learning relevance techniques

According to an implementation, a system includes a social media messaging platform configured to exchange messages, over a network, among a plurality of computing devices. The exchange of messages is based on a connection graph stored on the messaging platform. The social media messaging platform includes a registration manager configured to register an account for an entity to boost a social media presence of the entity on the social media messaging platform, and a social media presence booster having a machine-learning relevance engine configured to programmatically match the entity's content with relevant entities. The social media presence booster is configured to automatically and programmatically boost the entity's content to the relevant entities, and increase, over time, a number of connections in the connection graph between the account and other accounts on the social media messaging platform in response to the boosted content.

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Belmont, CA, United States of America

Kelly Huffman