SYSTEMS AND METHODS FOR SHARING CONTENT

1 . A computer-implemented method comprising:

providing, by a computing system, a scalable composer interface that includes an option to access a menu of options;

determining, by the computing system, a content item being composed in the scalable composer interface;

predicting, by the computing system, at least one option to be included in the scalable composer interface based at least in part on a machine learning model that evaluates the content item being composed, wherein the at least one option is predicted based at least in part on (i) a set of features associated with the content item and (ii) a user composing the content item, and wherein the at least one option can be selected to insert content into the content item, wherein the predicting the at least one option comprises:

training, by the computing system, the machine learning model based on training data that includes training examples including supervisory signals associated with options selected by users to insert content into content items; and

providing, by the computing system, an updated scalable composer interface that includes (i) the at least one option and (ii) the option to access the menu of options.

2 . The computer-implemented method of claim 1 , wherein the content item includes a post and predicting the at least one option further comprises:

determining, by the computing system, a type of the post, wherein the at least one option is determined based at least in part on the type of the post.

3 . The computer-implemented method of claim 2 , wherein the type of the post corresponds to at least one of a post that references external content, a post that solicits information, or a post that includes a call-to-action.

4 . The computer-implemented method of claim 1 , wherein predicting the at least one option further comprises:

determining, by the computing system, subject matter included in the content item, wherein the at least one option is determined based at least in part on the subject matter included in the content item, wherein the subject matter includes at least one of text included with the content item, visual content included with the content item, or a combination thereof.

5 . (canceled)

6 . (canceled)

7 . (canceled)

8 . The computer-implemented method of claim 1 , wherein the training examples further include at least content item types and subject matter included in the content items.

9 . The computer-implemented method of claim 7 , wherein the machine learning model is trained to predict the at least one option based in part on an identity of the user accessing the scalable composer interface.

10 . The computer-implemented method of claim 1 , further comprising:

determining, by the computing system, a selection of an option in the scalable composer interface to compose a second content item;

predicting, by the computing system, at least one option for the second content item; and

providing, by the computing system, the at least one option in the scalable composer interface, wherein the at least one predicted option can be selected to create and share the second content item.

11 . A system comprising:

at least one processor; and

a memory storing instructions that, when executed by the at least one processor, cause the system to perform:

providing a scalable composer interface that includes an option to access a menu of options;

determining a content item being composed in the scalable composer interface;

predicting at least one option to be included in the scalable composer interface based at least in part on a machine learning model that evaluates the content item being composed, wherein the at least one option is predicted based at least in part on (i) a set of features associated with the content item and (ii) a user composing the content item, and wherein the at least one option can be selected to insert content into the content item, wherein the predicting the at least one option comprises:

training the machine learning model based on training data that includes training examples including supervisory signals associated with options selected by users to insert content into content items; and

providing an updated scalable composer interface that includes (i) the at least one option and (ii) the option to access the menu of options.

12 . The system of claim 11 , wherein predicting the at least one option further causes the system to perform:

determining a type of the post, wherein the at least one option is determined based at least in part on the type of the post.

13 . The system of claim 12 , wherein the type of the post corresponds to at least one of a post that references external content, a post that solicits information, or a post that includes a call-to-action.

14 . The system of claim 11 , wherein predicting the at least one option further causes the system to perform:

determining subject matter included in the content item, wherein the at least one option is determined based at least in part on the subject matter included in the content item, wherein the subject matter includes at least one of text included with the content item, visual content included with the content item, or a combination thereof.

15 . (canceled)

16 . A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising:

providing a scalable composer interface that includes an option to access a menu of options;

determining a content item being composed in the scalable composer interface;

predicting at least one option to be included in the scalable composer interface based at least in part on a machine learning model that evaluates the content item being composed, wherein the at least one option is predicted based at least in part on (i) a set of features associated with the content item and (ii) a user composing the content item, and wherein the at least one option can be selected to insert content into the content item, wherein the predicting the at least one option comprises:

training the machine learning model based on training data that includes training examples including supervisory signals associated with options selected by users to insert content into content items; and

providing an updated scalable composer interface that includes (i) the at least one option and (ii) the option to access the menu of options.

17 . The non-transitory computer-readable storage medium of claim 16 , wherein predicting the at least one option further causes the computing system to perform:

determining a type of the post, wherein the at least one option is determined based at least in part on the type of the post.

18 . The non-transitory computer-readable storage medium of claim 17 , wherein the type of the post corresponds to at least one of a post that references external content, a post that solicits information, or a post that includes a call-to-action.

19 . (canceled)

20 . (canceled)

21 . The computer-implemented method of claim 1 , wherein the content for insertion into the content item includes at least one of an interactive sticker, an image, a video, or a graphical effect.

22 . The computer-implemented method of claim 1 , wherein the content item is a post for posting on a social networking system and the at least one option of the updated scalable composer interface is selected to insert the content into the post.

23 . The computer-implemented method of claim 1 , wherein the at least one option is predicted when the user is creating the content item.

24 . The computer-implemented method of claim 23 , wherein the at least one option is predicted after the user enters text during creation of the content item.

25 . The computer-implemented method of claim 1 , wherein

the at least one option further includes a second option to access a camera interface,

the training the machine learning model is further based on training data that includes training examples including supervisory signals associated with options selected by users to access camera interfaces, and

the updated scalable content interface includes the second option.