Contextual determination of emotion icons

1. A method comprising:

generating, by one or more processors, a plurality of emotion icons, wherein the plurality of emotion icons is based on a class of a user, a class of a recipient, one or more facial parameters of the user, and one or more facial parameters of the recipient, wherein the class of the user is based on a current state of the user and a cognitive style of the user, wherein the class of the recipient is based on a current state of the recipient and a cognitive style of the recipient, wherein a current state of the user includes a current emotional state of the user, and wherein a cognitive style of the user reflects the user's cultural norms, demographic, and mental conditions;

determining, by one or more processors, for a user, at least one emotion icon among the plurality of emotion icons to automatically input into a message based on the class of the user, the class of the recipient and a context of the message;

inserting, by the one or more processors, the determined at least one emotion icon among the generated plurality of emotion icons into the message in response to determining the context of the message; and

generating, by the one or more processors, a new emotion icon from the generated plurality of emotion icons based on the one or more facial parameters and the determined context of the message.

2. The method of claim 1 , wherein generating the new emotion icon, comprises:

learning, by the one or more processors, communications patterns between the user and the recipient of the message, wherein the learned communication patterns are incorporated into the context by performing analytics.

3. The method of claim 2 , wherein the learned communication patterns of the user and the recipient are based, in part, on: text analysis associated with used emotion icons and the class of the user, wherein the text analysis is incorporated into the context of the message by performing analytics.

4. The method of claim 1 , wherein determining the at least one emotion icon further comprises:

from a user input, converting the user input to at least one emotion icon that is recognizable to the recipient, based on the class of the recipient.

5. The method of claim 1 , wherein determining at least one emotion icon for a user to input into the message further comprises:

generating, by the one or more processors, a list of emotion icons, wherein the list of emotion icons are: (i) selectable by the user, and (ii) incorporated into the plurality of emotion icons, wherein the list of emotion icons are generated based on a type of social interaction between the user and the recipient, and wherein the type of social interaction between the user and the recipient are incorporated into the context of the message by performing analytics.

6. The method of claim 1 , further comprising:

based on the class of the user and the recipient, embedding at least one emotion icon into the message, wherein the embedded at least one emotion icon is visible to the recipient responsive to a mouse hover gesture.

7. The method of claim 1 , further comprising:

receiving, by the one or more processors, feedback from at least the user or the recipient, based on the determined at least one emotion icon among the plurality of emotion icons inserted into the message, wherein receiving feedback comprises a user selection of a GUI associated with an e-mail or instant messaging system;

determining, by the one or more processors, whether an emotion icon among the plurality of emotions icons is unnecessary in the message based on the determined context performed by analytics; and

in response to determining that the emotion icon among the plurality of emotion icons is unnecessary in the message, removing, by the one or more processors, the emotion icon from the message.

8. The method of claim 1 , wherein generating a plurality of emotion icons is further based on audio input comprising one or more sounds different from speech of the user.

9. The method of claim 8 , wherein generating a plurality of emotion icons comprises identifying context of a conversation based on the audio input of the user.

10. A computer program product comprising:

a computer readable storage medium and program instructions stored on the computer readable storage medium, the program instructions comprising:

program instructions to generate a plurality of emotion icons, wherein the plurality of emotion icons is based on a class of a user, a class of a recipient, one or more facial parameters of the user, and one or more facial parameters of the recipient, wherein the class of the user is based on a current state of the user and a cognitive style of the user, wherein the class of the recipient is based on a current state of the recipient and a cognitive style of the recipient, wherein a current state of the user includes a current emotional state of the user, and wherein a cognitive style of the user reflects the user's cultural norms, demographic, and mental conditions;

program instructions to determine, for a user, at least one emotion icon among the plurality of emotion icons to automatically input into a message based on the class of the user, the class of the recipient and a context of the message;

program instructions to insert the determined at least one emotion icon among the generated plurality of emotion icons into the message in response to determining the context of the message; and

program instructions to generate a new emotion icon from the generated plurality of emotion icons based on the one or more facial parameters and the determined context of the message.

11. The computer program product of claim 10 , wherein the program instructions to generate the new emotion icon, comprise:

program instructions to learn communications patterns between the user and the recipient of the message, wherein the learned communication patterns are incorporated into the context of the message by performing analytics.

12. The computer program product of claim 11 , wherein the learned communication patterns of the user and the recipient are based, in part, on: text analysis associated with used emotion icons and the class of the user, wherein the text analysis is incorporated into the context of the message by performing analytics.

13. The computer program product of claim 10 , wherein the program instructions to determine the at least one emotion icon further comprise:

program instructions to convert a user input to at least one emotion icon that is recognizable to the recipient, based on the class of the recipient.

14. The computer program product of claim 10 , wherein the program instructions to determine at least one emotion icon for a user to input into the message further comprise:

program instructions to generate a list of emotion icons, wherein the list of emotion icons are: (i) selectable by the user and (ii) incorporated into the plurality of emotion icons, wherein the list of emotion icons are generated based on a type of social interaction between the user and the recipient, and wherein the type of social interaction between the user and the recipient are incorporated into the context of the message by performing analytics.

15. The computer program product of claim 10 , further comprising:

program instructions to receive feedback from at least the user or the recipient, based on the determined at least one emotion icon among the plurality of emotion icons inserted into the message, wherein the program instructions to receive feedback comprise a user selection of a GUI associated with an e-mail or instant messaging system;

program instructions to determine whether an emotion icon among the plurality of emotion icons is unnecessary in the message based on the determined context performed by analytics; and

program instructions to, in response to determining that the emotion icon among the plurality of emotion icons is unnecessary in the message, remove the emotion icon from the message.

16. The computer program product of claim 10 , wherein the program instructions to generate a plurality of emotion icons is further based on audio input comprising one or more sounds different from speech of the user.

17. A computer system comprising:

one or more computer processors;

one or more computer readable storage media;

program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising:

program instructions to generate a plurality of emotion icons, wherein the plurality of emotion icons is based on a class of a user, a class of a recipient, one or more facial parameters of the user, and one or more facial parameters of the recipient, wherein the class of the user is based on a current state of the user and a cognitive style of the user, wherein the class of the recipient is based on a current state of the recipient and a cognitive style of the recipient, wherein a current state of the user includes a current emotional state of the user, and wherein a cognitive style of the user reflects the user's cultural norms, demographic, and mental conditions;

program instructions to determine, for a user, at least one emotion icon among the plurality of emotion icons to automatically input into a message based on the class of the user, the class of the recipient and a context of the message;

program instructions to insert the determined at least one emotion icon among the generated plurality of emotion icons into the message in response to determining the context of the message; and

program instructions to generate a new emotion icon from the generated plurality of emotion icons based on the one or more facial parameters and the determined context of the message.

18. The computer system of claim 17 , wherein the program instructions to generate the new emotion icon, comprise:

program instructions to learn communications patterns between the user and the recipient of the message, wherein the learned communication patterns are incorporated into the context of the message by performing analytics.

19. The computer system of claim 18 , wherein the learned communication patterns of the user and the recipient are based, in part, on: text analysis associated with used emotion icons and the class of the user, wherein the text analysis is incorporated into the context of the message by performing analytics.

20. The computer system of claim 17 , wherein the program instructions to determine the at least one emotion icon further comprise:

program instructions to convert a user input to at least one emotion icon that is recognizable to the recipient, based on the class of the recipient.