Systems and methods for identifying and inserting emoticons
Computer-implemented systems and methods are provided for suggesting emoticons for insertion into text based on an analysis of sentiment in the text. An example method includes: determining a first sentiment of text in a text field; selecting first text from the text field in proximity to a current position of an input cursor in the text field; identifying one or more candidate emoticons wherein each candidate emoticon is associated with a respective score indicating relevance to the first text and the first sentiment based on, at least, historical user selections of emoticons for insertion in proximity to respective second text having a respective second sentiment; providing one or more candidate emoticons having respective highest scores for user selection; and receiving user selection of one or more of the provided emoticons and inserting the selected emoticons into the text field at the current position of the input cursor.
1. A method, comprising:
determining a first sentiment of a text received from a user;
calculating sentiment similarity scores based on a similarity between the first sentiment and a respective second sentiment of each of a plurality of candidate emoticons;
identifying one or more of the candidate emoticons having a closest similarity to the first sentiment based on the sentiment similarity scores;
providing the one or more candidate emoticons for selection by the user;
receiving the selection of one of the candidate emoticons by the user; and
inserting the selected candidate emoticon into the text.
2. The method of claim 1 , wherein the selected candidate emoticon is inserted at a current position of an input cursor in the text.
3. The method of claim 1 , wherein providing the one or more candidate emoticons for selection by the user comprises:
presenting the candidate emoticon for selection by the user at or near a current position of an input cursor in the text.
4. The method of claim 1 , comprising:
determining a respective popularity of the candidate emoticons.
5. The method of claim 4 , wherein the sentiment similarity score is based at least in part on the popularity of the candidate emoticon.
6. The method of claim 1 , comprising:
determining that the text is associated with a brand, a product, or a service; and, based thereon,
identifying the candidate emoticon for the brand, the product, or the service.
7. The method of claim 1 , comprising:
performing sentiment analysis to determine the first sentiment of the text.
8. The method of claim 7 , wherein performing sentiment analysis to determine the first sentiment of the text comprises:
analyzing the text in real-time as the text is being entered by the user.
9. The method of claim 1 , wherein the first sentiment is associated with an attitude of the user with respect to a topic described in the text.
10. The method of claim 1 , wherein identifying one or more of the candidate emoticons having a closet sentiment similarity score to the first sentiment is further based on at least one of a preference of the user, user-related information, or recipient-related information.
11. A system, comprising:
one or more computer processors programmed to perform operations to:
determine a first sentiment of a text received from a user;
calculate sentiment similarity scores based on a similarity between the first sentiment and a respective second sentiment of each of a plurality of candidate emoticons;
identify one or more of the candidate emoticons having a closest similarity to the first sentiment based on the sentiment similarity scores;
provide the one or more candidate emoticons for selection by the user;
receive the selection of one of the candidate emoticons by the user; and
insert the selected candidate emoticon into the text.
12. The system of claim 11 , wherein the selected candidate emoticon is inserted at a current position of an input cursor in the text.
13. The system of claim 11 , wherein to provide the one or more candidate emoticons for selection by the user the one or more computer processors are further to:
present the candidate emoticon for selection by the user at or near a current position of an input cursor in the text.
14. The system of claim 11 , wherein the operations are further to:
determine a respective popularity of the candidate emoticons.
15. The system of claim 14 , wherein the sentiment similarity score is based at least in part on the popularity of the candidate emoticon.
16. The system of claim 11 , wherein the operations are further to:
determine that the text is associated with a brand, a product, or a service; and, based thereon,
identify the candidate emoticon for the brand, the product, or the service.
17. The system of claim 11 , wherein the operations are further to:
perform sentiment analysis to determine the first sentiment of the text.
18. The system of claim 17 , wherein to perform sentiment analysis to determine the first sentiment of the text the one or more computer processors are further to:
analyze the text in real-time as the text is being entered by the user.
19. The system of claim 11 , wherein the first sentiment is associated with an attitude of the user with respect to a topic described in the text.
20. A non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more computer processors, cause the one or more computer processors to:
determine a first sentiment of a text received from a user;
calculate sentiment similarity scores based on a similarity between the first sentiment and a respective second sentiment of each of a plurality of candidate emoticons;
identify one or more of the candidate emoticons having a closest similarity to the first sentiment based on the sentiment similarity scores;
provide the one or more candidate emoticons for selection by the user;
receive the selection of one of the candidate emoticons by the user; and
insert the selected candidate emoticon into the text.