Automated categorization of groups in a social network

1. A computer-implemented method, comprising:

accessing content shared within a first group in a social network application;

processing the shared content with at least one machine learning model to determine one or more labels for the content;

determining one or more categories for the first group based on the one or more labels for the content;

accessing one or more categories for a second group of the social network application;

generating a match between the first group and the second group based on the one or more categories for the first group and the one or more categories for the second group;

supplying data indicative of the match to a client device of a user in the second group;

receiving a match acceptance from the client device; and

in response to receiving the match acceptance, combining the first group and the second group in the social network application.

2. The method of claim 1 , wherein the content comprises at least one of text, audio, image, or video data shared within the first group.

3. The method of claim 1 , wherein the first group comprises two or more users of the social network application, and wherein the content comprises content shared by at least one of the two or more users in a communication channel associated with the first group.

4. The method of claim 3 , wherein the communication channel comprises at least one of a group chat, a group web page, or a group streaming channel.

5. The method of claim 1 , wherein the at least one machine learning model is selected from a plurality of machine learning models based on a type of the content, with the type of content comprising at least one of text, audio, image, or video.

6. The method of claim 1 , further comprising:

in response to receiving the match acceptance, providing the user in the second group access to the first group in the social network application,

wherein providing the user in the second group access to the first group in the social network application comprises enabling network communication between the user in the second group and the first group or enabling the user in the second group to share content with the first group.

7. The method of claim 1 , further comprising:

supplying data indicative of the match to at least one client device associated with at least one user in the second group;

receiving a match acceptance from the at least one client device; and

in response to receiving the match acceptance, providing the user in the second group access to the first group in the social network application.

8. The method of claim 1 , wherein the one or more categories for the first group comprise a subset of the one or more labels for the content.

9. The method of claim 1 , wherein the at least one machine learning model is trained based on labeled content received from one or more users in the first group of the social network application.

10. The method of claim 1 , wherein the content comprises streamed video content, and wherein processing the shared content with the at least one machine learning model to determine the one or more labels for the content comprises:

analyzing the streamed video content in real-time or near-real time, or

analyzing a copy of the streamed video content after a streaming of the streamed video content has ended.

11. A computer-implemented method, comprising:

for each of a plurality of groups in a social network application:

accessing content shared within a group;

processing the shared content with at least one machine learning model to determine one or more labels for the content; and

determining one or more categories for the group based on the one or more labels for the content;

generating a match between a first group and a second group of the plurality of groups based on the one or more categories for each of the first group and the second group;

supplying data indicative of the match to each of the first group and the second group;

receiving a match acceptance from at least one of the first group or the second group; and

in response to receiving the match acceptance, combining the first group and the second group, wherein each of the first group and the second group comprise two or more users.

12. The method of claim 11 , wherein the content comprises at least one of text, audio, image, or video data shared within the group.

13. The method of claim 11 , wherein the content comprises content shared by at least one of the two or more users in a communication channel associated with the group.

14. The method of claim 13 , wherein the communication channel comprises at least one of a group chat, a group web page, or a group streaming channel.

15. The method of claim 11 , wherein the at least one machine learning model is selected from a plurality of machine learning models based on a type of the content, with the type of content comprising at least one of text, audio, image, or video.

16. The method of claim 11 , wherein the data indicative of the match comprises a prompt to combine the first group and the second group.

17. The method of claim 11 , wherein combining the first group and the second group comprises adding members of the first group to the second group, or creating a third group with the members of the first group and members of the second group.

18. The method of claim 11 , wherein the content comprises streamed video content, and wherein processing the shared content with the at least one machine learning model to determine the one or more labels for the content comprises:

analyzing the streamed video content in real-time or near-real time, or

analyzing a copy of the streamed video content after a streaming of the streamed video content has ended.