Artificial intelligence communication assistance for improving the effectiveness of communications using reaction data

1. A method of electronic communication assistance, the method comprising:

obtaining a copy of an in-transit electronic communication at an artificial intelligence assistant computing facility, wherein the electronic communication was transmitted from a first electronic identifier associated with a first user to a second electronic identifier associated with a second user, the electronic communication comprising a communication content and comprising or associated with the first electronic identifier associated with the first user;

extracting a communication context from the electronic communication;

encoding the electronic communication for processing creating an encoded electronic communication;

retrieving from a communication profile database a communication profile for the second user utilizing the second electronic identifier, wherein the communication profile comprises a second user communication attribute;

receiving electronic reaction data from a second electronic identifier of the second user, wherein the electronic reaction data is generated in response to the second user receiving the electronic communication;

encoding the electronic reaction data for processing creating an encoded electronic reaction data;

processing the encoded electronic communication and the encoded electronic reaction data to extract a reaction context with a processor to generate a response feedback communication using at least one of the communication content, the extracted communication context, or the second user communication attribute;

sending the response feedback communication to the first electronic identifier; and

sharing the reaction context with a subset of other users who received the electronic communication;

wherein the electronic reaction data corresponds to an emoji selected by the second user after highlighting a fragment of a sentence of the electronic communication.

2. The method of claim 1 , wherein the response feedback communication is derived at least in part from representations of previous electronic communications from a plurality of user profiles stored in the communication profile database which are similar to the-communication profile for the second user.

3. The method of claim 1 , wherein the response feedback communication is derived at least in part from representations of previous electronic communications from a plurality of user profiles stored in the communication profile database which are similar to a communication profile of the first user.

4. The method of claim 1 , wherein the processor utilizes at least one of a machine learning language model or a statistical algorithm for creating the response feedback communication.

5. The method of claim 1 , wherein the electronic communication further comprises a communication goal, and the processor generates the response feedback communication at least in part by computing and utilizing a reaction difference attribute derived from determined differences between the communication goal and the electronic reaction data.

6. The method of claim 1 , wherein the electronic reaction data comprises at least one of location information for the second user, or an action taken by the second user.

7. The method of claim 1 , wherein the reaction context comprises an emotional state of the second user.

8. The method of claim 1 , wherein the electronic reaction data is used to generate an updated second communication profile.

9. The method of claim 8 , wherein the updated second communication profile is used to predict a most likely reaction outcome in a second electronic communication.

10. The method of claim 1 , wherein the electronic reaction data is used to train a machine learning model that is configured to at least one of generate a communication content or modify a communication content.

11. A system comprising:

a server computer comprising a processor and a computer-readable storage device that stores instructions that, when executed by the processor, cause the processor to perform operations comprising:

obtaining a copy of an in-transit electronic communication at an artificial intelligence assistant computing facility, wherein the electronic communication was transmitted from a first electronic identifier associated with a first user to a second electronic identifier associated with a second user, the electronic communication comprising a communication content and comprising or associated with the first electronic identifier associated with the first user;

extracting a communication context from the electronic communication;

encoding the electronic communication for processing creating an encoded electronic communication;

retrieving from a communication profile database a communication profile for the second user utilizing the second electronic identifier, wherein the communication profile comprises a second user communication attribute;

receiving electronic reaction data from a second electronic identifier of the second user, wherein the electronic reaction data is generated in response to the second user receiving the electronic communication;

encoding the electronic reaction data for processing creating an encoded electronic reaction data;

processing the encoded electronic communication and the encoded electronic reaction data to extract a reaction context with a processor to generate a response feedback communication using at least one of the communication content, the extracted communication context, or the second user communication attribute;

sending the response feedback communication to the first electronic identifier; and

sharing the reaction context with a subset of other users who received the electronic communication;

wherein the electronic reaction data corresponds to an emoji selected by the second user after highlighting a fragment of a sentence of the electronic communication.

12. The system of claim 11 , wherein the response feedback communication is derived at least in part from representations of previous electronic communications from a plurality of user profiles stored in the communication profile database which are similar to the-communication profile for the second user.

13. The system of claim 11 , wherein the response feedback communication is derived at least in part from representations of previous electronic communications from a plurality of user profiles stored in the communication profile database which are similar to a communication profile of the first user.

14. The system of claim 11 , wherein the processor utilizes at least one of a machine learning language model or a statistical algorithm for creating the response feedback communication.

15. The system of claim 11 , wherein the electronic communication further comprises a communication goal, and the processor generates the response feedback communication at least in part by computing and utilizing a reaction difference attribute derived from determined differences between the communication goal and the electronic reaction data.

16. The system of claim 11 , wherein the electronic reaction data comprises at least one of location information for the second user, or an action taken by the second user.

17. The system of claim 11 , wherein the reaction context comprises an emotional state of the second user.

18. The system of claim 11 , wherein the electronic reaction data is used to generate an updated second communication profile.

19. The system of claim 18 , wherein the updated second communication profile is used to predict a most likely reaction outcome in a second electronic communication.

20. The system of claim 11 , wherein the electronic reaction data is used to train a machine learning model that is configured to at least one of generate a communication content or modify a communication content.