Streaming platforms and websites media discovery engine and recommendation integration system and method

1 . A method, comprising:

receiving, by a computer system, an activation of group mode from a first user device associated with a first user included in a group that includes a plurality of users;

sending, by the computer system, a first content recommendation to a respective plurality of user devices associated with the plurality of users;

receiving, by the computer system from the respective plurality of user devices, first data indicative of a user decision from the first user regarding the first content recommendation;

selecting, by the computer system based on a type of content in which the first content recommendation is included, a combination of at least two analysis algorithms: collaborative filtering, content-based filtering, supervised learning, deep learning, reinforcement learning, A/B testing, natural language processing, or Bayesian ranking;

determining, by the computer system, a second content recommendation using the respective plurality of user devices associated with the plurality of users;

sending, by the computer system, the second content recommendation to the respective plurality of user devices;

comparing a number of affirmative decisions received from the plurality of users for the first content recommendation to a threshold value, wherein the threshold value is associated with a type of group identified in the activation of the group mode; and

in response to the number of affirmative decisions exceeding the threshold value, halting a determination of new content recommendations to the type of group identified in the activation of the group mode.

2 . The method of claim 1 , wherein the activation of the group mode is associated with a friend group of the first user, wherein the plurality of users is included within the friend group of the first user, and wherein user decisions of the plurality of users in the friend group are stored in a group information data store in the computer system.

3 . The method of claim 1 , wherein the activation of the group mode is associated with a family group of the first user, wherein the plurality of users is included within the family group of the first user, and wherein user decisions of the plurality of users in the family group are stored in a group information data store in the computer system.

4 . The method of claim 1 , further comprising:

determining a first threshold value for a first group in a first type of group identified in the activation of the group mode and a second threshold value for a second group in a second type of group identified in the activation of the group mode; and

in response to receiving a number of affirmative decisions to the first content recommendation for the first threshold value and not the second threshold value, halting a determination of new content recommendations to the second group and sending a link to a piece of content associated with the first group.

5 . The method of claim 1 , wherein the first data indicative of the user decision includes information regarding a gesture made on a touchscreen included in the first user device.

6 . The method of claim 5 , wherein the gesture includes a swipe across the touchscreen in a particular direction.

7 . The method of claim 1 , wherein the first content recommendation is associated with a first content category, and further comprising:

receiving, by the computer system, a content category switch request to a second content category; and

sending, by the computer system, a third content recommendation to the first user device, wherein the third content recommendation is associated with the second content category.

8 . A system, comprising:

one or more memory circuits configured to store instructions; and

one or more processors configured to receive instructions from the one or more memory circuits and execute the instructions to cause the system to perform operations comprising:

receiving, by a computer system, an activation of group mode from a first user device associated with a first user included in a group that includes a plurality of users;

sending, by the computer system, a first content recommendation to a respective plurality of user devices associated with the plurality of users;

receiving, by the computer system from the respective plurality of user devices, first data indicative of a user decision from the first user regarding the first content recommendation;

selecting, by the computer system based on a type of content in which the first content recommendation is included, a combination of at least two analysis algorithms: collaborative filtering, content-based filtering, supervised learning, deep learning, reinforcement learning, A/B testing, natural language processing, or Bayesian ranking;

determining, by the computer system, a second content recommendation using the respective plurality of user devices associated with the plurality of users;

sending, by the computer system, the second content recommendation to the respective plurality of user devices;

comparing a number of affirmative decisions received from the plurality of users for the first content recommendation to a first threshold value, wherein the first threshold value is associated with a type of group identified in the activation of the group mode; and

in response to the number of affirmative decisions exceeding the first threshold value, halting a determination of new content recommendations to the type of group identified in the activation of the group mode.

9 . The system of claim 8 , wherein the activation of the group mode is associated with a friend group of the first user, wherein the plurality of users is included within the friend group of the first user, and wherein user decisions of the plurality of users in the friend group are stored in a group information data store in the computer system.

10 . The system of claim 8 , wherein the activation of the group mode is associated with a family group of the first user, wherein the plurality of users is included within the family group of the first user, and wherein user decisions of the plurality of users in the family group are stored in a group information data store in the computer system.

11 . The system of claim 8 , wherein the operations further include:

comparing a number of affirmative decisions received from the plurality of users for the first content recommendation to a second threshold value, wherein the second threshold value is associated with a type of group identified in the activation of the group mode; and

in response to the number of affirmative decisions exceeding the second threshold value, halting a determination of new content recommendations to the type of group identified in the activation of the group mode.

12 . The system of claim 8 , wherein the first data indicative of the user decision includes information regarding a gesture made on a touchscreen included in the first user device.

13 . The system of claim 12 , wherein the gesture includes a swipe across the touchscreen in a particular direction.

14 . The system of claim 8 , wherein the first content recommendation is associated with a first content category, and the operations further include:

receiving, by the computer system, a content category switch request to a second content category; and

sending, by the computer system, a third content recommendation to the first user device, wherein the third content recommendation is associated with the second content category.

15 . A non-transitory computer-accessible storage medium having program instructions stored therein that, in response to execution by a computer system, causes the computer system to perform operations including:

receiving, by the computer system, an activation of group mode from a first user device associated with a first user included in a group that includes a plurality of users;

sending, by the computer system, a first content recommendation to a respective plurality of user devices associated with the plurality of users;

receiving, by the computer system from the respective plurality of user devices, first data indicative of a user decision from the first user regarding the first content recommendation;

selecting, by the computer system based on a type of content in which the first content recommendation is included, a combination of at least two analysis algorithms: collaborative filtering, content-based filtering, supervised learning, deep learning, reinforcement learning, A/B testing, natural language processing, or Bayesian ranking;

determining, by the computer system, a second content recommendation using the respective plurality of user devices associated with the plurality of users;

sending, by the computer system, the second content recommendation to the respective plurality of user devices;

comparing a number of affirmative decisions received from the plurality of users for the first content recommendation to a threshold value, wherein the threshold value is associated with a type of group identified in the activation of the group mode; and

in response to the number of affirmative decisions exceeding the threshold value, halting a determination of new content recommendations to the type of group identified in the activation of the group mode.

16 . The non-transitory computer-accessible storage medium of claim 15 , wherein the activation of the group mode is associated with a friend group of the first user, wherein the plurality of users is included within the friend group of the first user, and wherein user decisions of the plurality of users in the friend group are stored in a group information data store in the computer system.

17 . The non-transitory computer-accessible storage medium of claim 15 , wherein the activation of the group mode is associated with a family group of the first user, wherein the plurality of users is included within the family group of the first user, and wherein user decisions of the plurality of users in the family group are stored in a group information data store in the computer system.