SYSTEMS AND METHODS FOR PROVIDING DYNAMIC HOVERCARDS ASSOCIATED WITH PAGES IN A SOCIAL NETWORKING SYSTEM
Systems, methods, and non-transitory computer readable media can receive a request to generate a hovercard associated with a page of a social networking system for a user. One or more of textual content items associated with the page, multimedia content items associated with the page, or actions associated with the page can be ranked for the user, based on one or more machine learning models. The hovercard associated with the page can be dynamically generated for the user for display, based on the ranked textual content items, multimedia content items, or actions.
1 . A computer-implemented method comprising:
receiving, by a computing system, a request to generate a hovercard associated with a page of a social networking system for a user;
ranking, by the computing system, for the user, based on one or more machine learning models, one or more of: textual content items associated with the page, multimedia content items associated with the page, or actions associated with the page; and
dynamically generating, by the computing system, the hovercard associated with the page for the user for display, based on the ranked textual content items, multimedia content items, or actions.
2 . The computer-implemented method of claim 1 , wherein the request to generate the hovercard is generated in response to detection of a hovering action in connection with page information displayed on a particular surface.
3 . The computer-implemented method of claim 1 , wherein the ranking includes:
training a machine learning model to rank textual content items associated with pages; and
ranking the textual content items associated with the page based on the trained machine learning model.
4 . The computer-implemented method of claim 1 , wherein the ranking includes:
training a machine learning model to rank multimedia content items associated with pages; and
ranking the multimedia content items associated with the page based on the trained machine learning model.
5 . The computer-implemented method of claim 1 , wherein the ranking includes:
training a machine learning model to rank actions associated with pages; and
ranking the actions associated with the page based on the trained machine learning model.
6 . The computer-implemented method of claim 1 , wherein the ranking includes:
training a machine learning model to rank pairs of textual content items and multimedia content items associated with pages; and
ranking pairs of the textual content items associated with the page and the multimedia content items associated with the page based on the trained machine learning model.
7 . The computer-implemented method of claim 1 , wherein the hovercard includes a page header, one or more ranked textual content items associated with the page, one or more ranked multimedia content items associated with the page, and one or more ranked actions associated with the page.
8 . The computer-implemented method of claim 1 , wherein the ranking is based on a likelihood of the user engaging with an action to be included in the hovercard.
9 . The computer-implemented method of claim 1 , wherein the ranking is based on one or more of: display features, content features, viewer intent features, or admin intent features.
10 . The computer-implemented method of claim 1 , wherein
the textual content items associated with the page include one or more of: a page description, a link, a post, a review, or a social context;
the multimedia content items associated with the page include one or more of: a photo, a video, or a map preview; and
the actions associated with the page include one or more of: like, follow, save, share, message, or a call-to-action (CTA).
11 . A system comprising:
at least one hardware processor; and
a memory storing instructions that, when executed by the at least one processor, cause the system to perform:
receiving a request to generate a hovercard associated with a page of a social networking system for a user;
ranking for the user, based on one or more machine learning models, one or more of: textual content items associated with the page, multimedia content items associated with the page, or actions associated with the page; and
dynamically generating the hovercard associated with the page for the user for display, based on the ranked textual content items, multimedia content items, or actions.
12 . The system of claim 11 , wherein the ranking includes:
training a machine learning model to rank textual content items associated with pages; and
ranking the textual content items associated with the page based on the trained machine learning model.
13 . The system of claim 11 , wherein the ranking includes:
training a machine learning model to rank multimedia content items associated with pages; and
ranking the multimedia content items associated with the page based on the trained machine learning model.
14 . The system of claim 11 , wherein the ranking includes:
training a machine learning model to rank actions associated with pages; and
ranking the actions associated with the page based on the trained machine learning model.
15 . The system of claim 11 , wherein the hovercard includes a page header, one or more ranked textual content items associated with the page, one or more ranked multimedia content items associated with the page, and one or more ranked actions associated with the page.
16 . A non-transitory computer readable medium including instructions that, when executed by at least one hardware processor of a computing system, cause the computing system to perform a method comprising:
receiving a request to generate a hovercard associated with a page of a social networking system for a user;
ranking for the user, based on one or more machine learning models, one or more of: textual content items associated with the page, multimedia content items associated with the page, or actions associated with the page; and
dynamically generating the hovercard associated with the page for the user for display, based on the ranked textual content items, multimedia content items, or actions.
17 . The non-transitory computer readable medium of claim 16 , wherein the ranking includes:
training a machine learning model to rank textual content items associated with pages; and
ranking the textual content items associated with the page based on the trained machine learning model.
18 . The non-transitory computer readable medium of claim 16 , wherein the ranking includes:
training a machine learning model to rank multimedia content items associated with pages; and
ranking the multimedia content items associated with the page based on the trained machine learning model.
19 . The non-transitory computer readable medium of claim 16 , wherein the ranking includes:
training a machine learning model to rank actions associated with pages; and
ranking the actions associated with the page based on the trained machine learning model.
20 . The non-transitory computer readable medium of claim 16 , wherein the hovercard includes a page header, one or more ranked textual content items associated with the page, one or more ranked multimedia content items associated with the page, and one or more ranked actions associated with the page.