Communications channels in media systems

1. A method comprising:

receiving, from a first user device associated with a first user, one or more first keywords of interest for a media content item;

identifying a second user, for the first user to recommend the media content item to, based on a correlation value indicating a degree of association between the one or more first keywords of interest of the first user and one more second keywords of interest of the second user;

in response to the correlation value being above a threshold, establishing a communication link between the first user device and a second user device associated with the second user;

monitoring a communication between the first user and the second user correlating to the media content item;

determining a feedback score of the second user for the media content item based on monitoring facial expressions of the second user during the communication correlating to the media content item; and

updating the correlation value between the one or more first keywords of interest of the first user and the one more second keywords of interest of the second user based on the feedback score of the second user for the media content item.

2. The method of claim 1 , further comprising:

generating, based on the correlation value, output to the first user device that the first user recommend the media content item to the second user.

3. The method of claim 1 , further comprising:

determining a period of time since the first user and the second user have communicated; and

generating, based on the period of time, an output to the first user device that the first user recommend the media content item to the second user.

4. The method of claim 1 , further comprising:

monitoring the communication between the first user and the second user by:

analyzing one or more segments of the communication; and

assigning a segment score to the one or more segments, wherein the segment score indicates a positive emotion or negative emotion associated with the media content item.

5. The method of claim 4 , wherein the segment score is based on (a) words or expressions within the one or more segments, (b) voice quality of the second user within the one or more segments, or (c) facial expressions of the second user during the one or more segments.

6. The method of claim 4 , further comprising:

determining a first partial segment score of the segment score based on words or expressions with the one or more segments;

determining a second partial segment score based on a voice quality of the second user within the one or more segments; and

determining a third partial segment score based on facial expressions of the second user during the one or more segments.

7. The method of claim 6 , further comprising:

determining the segment score based on a combination of the first partial segment score, the second partial segment score, and the third partial segment score.

8. A non-transitory computer-readable medium storing instructions that, when executed by a computing system, cause the computing system to perform operations comprising:

receiving, from a first user device associated with a first user, one or more first keywords of interest for a media content item;

identifying a second user, for the first user to recommend the media content item to, based on a correlation value indicating a degree of association between the one or more first keywords of interest of the first user and one more second keywords of interest of the second user;

in response to the correlation value being above a threshold, establishing a communication link between the first user device and a second user device associated with the second user;

monitoring a communication between the first user and the second user correlating to the media content item;

determining a feedback score of the second user for the media content item based on monitoring facial expressions of the second user during the communication correlating to the media content item; and

updating the correlation value between the one or more first keywords of interest of the first user and the one more second keywords of interest of the second user based on the feedback score of the second user for the media content item.

9. The non-transitory computer-readable medium of claim 8 , wherein the operations further comprise:

generating, based on the correlation value, output to the first user device that the first user recommend the media content item to the second user.

10. The non-transitory computer-readable medium of claim 8 , wherein the operations further comprise:

determining a period of time since the first user and the second user have communicated; and

generating, based on the period of time, an output to the first user device that the first user recommend the media content item to the second user.

11. The non-transitory computer-readable medium of claim 8 , wherein the operations further comprise:

monitoring the communication between the first user and the second user by:

analyzing one or more segments of the communication; and

assigning a segment score to the one or more segments, wherein the segment score indicates a positive emotion or negative emotion associated with the media content item.

12. The non-transitory computer-readable medium of claim 11 , wherein the segment score is based on (a) words or expressions within the one or more segments, (b) voice quality of the second user within the one or more segments, or (c) facial expressions of the second user during the one or more segments.

13. The non-transitory computer-readable medium of claim 11 , wherein the operations further comprise:

determining a first partial segment score of the segment score based on words or expressions with the one or more segments;

determining a second partial segment score based on a voice quality of the second user within the one or more segments; and

determining a third partial segment score based on facial expressions of the second user during the one or more segments.

14. The non-transitory computer-readable medium of claim 13 , wherein the operations further comprise:

determining the segment score based on a combination of the first partial segment score, the second partial segment score, and the third partial segment score.

15. A system comprising:

one or more processors; and

one or more memories storing instructions that, when executed by the one or more processors, cause the system to perform a process comprising:

receiving, from a first user device associated with a first user, one or more first keywords of interest for a media content item;

identifying a second user, for the first user to recommend the media content item to, based on a correlation value indicating a degree of association between the one or more first keywords of interest of the first user and one more second keywords of interest of the second user;

in response to the correlation value being above a threshold, establishing a communication link between the first user device and a second user device associated with the second user;

monitoring a communication between the first user and the second user correlating to the media content item;

determining a feedback score of the second user for the media content item based on monitoring facial expressions of the second user during the communication correlating to the media content item; and

updating the correlation value between the one or more first keywords of interest of the first user and the one more second keywords of interest of the second user based on the feedback score of the second user for the media content item.

16. The system according to claim 15 , wherein the process further comprises:

generating, based on the correlation value, output to the first user device that the first user recommend the media content item to the second user.

17. The system according to claim 15 , wherein the process further comprises:

determining a period of time since the first user and the second user have communicated; and

generating, based on the period of time, an output to the first user device that the first user recommend the media content item to the second user.

18. The system according to claim 15 , wherein the process further comprises:

monitoring the communication between the first user and the second user by:

analyzing one or more segments of the communication; and

assigning a segment score to the one or more segments, wherein the segment score indicates a positive emotion or negative emotion associated with the media content item.

19. The system according to claim 18 , wherein the segment score is based on (a) words or expressions within the one or more segments, (b) voice quality of the second user within the one or more segments, or (c) facial expressions of the second user during the one or more segments.

20. The system according to claim 18 , wherein the process further comprises:

determining a first partial segment score of the segment score based on words or expressions with the one or more segments;

determining a second partial segment score based on a voice quality of the second user within the one or more segments; and

determining a third partial segment score based on facial expressions of the second user during the one or more segments.