Abstract: The present disclosure is directed to systems and methods to identify trending or temporally popular phrases based on aggregating multiple users' interactions with an aggregate of content. A server may receive identification of a plurality of clicks of encoded uniform resource locator (URL) links. The server may identify, for each of the plurality of clicks, in content identified from decoding the encoded URL links, a plurality of phrases that correspond to a predetermined set of keywords. The server may determine a velocity of clicks on content corresponding to each phrase of the plurality of phrases and identify a trend in one or more phrases of the plurality of phrases based on the velocity of clicks.

Abstract: The present disclosure is directed to systems and methods that score content, URLs, domains, phrases or any entity based on an expected relevance to an individual user which may be based on that user's previous engagement with digital resources. A server receives identification of a plurality of actions of a user, which may include a click by the user on a link associated with a digital resource of a plurality of digital resources. The server may receive identification of actions of the user to share one or more digital resources of the plurality of digital resources. The server may identify a plurality of keywords from content of the plurality of digital resources, classify patterns from the actions of the users and the keywords and generate, based on the pattern classification, a relevance score responsive to receiving a user identifier and a digital resource keyword.