Systems and methods for identifying and suggesting emoticons

• US 9,043,196 B1
• Filed: 07/07/2014
• Issued: 05/26/2015
• Est. Priority Date: 07/07/2014
• Status: Active Grant

• Current Assignee: Mz Ip Holdings, LLC (AppLovin Corporation)
• Original Assignee: Machine Zone, Inc. (AppLovin Corporation)
• Inventors: Leydon, Gabriel, Bojja, Nikhil
• Primary Examiner(s): Opsasnick, Michael N
• Application Number:
  US14/324,733
• Time in Patent Office: 323 Days
• Field of Search: 704/5, 704/4
• US Class Current: 704/4
• CPC Class Codes: G06F 3/0219 Special purpose keyboards
• CPC Class Codes: G06F 3/0238 Programmable keyboards key guide holders G06F3/0224
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 40/166 Editing, e.g. inserting or deleting
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06F 40/20 Natural language analysis semantic analysis of natural language G06F40/30
• CPC Class Codes: G06F 40/226 Validation
• CPC Class Codes: G06F 40/253 Grammatical analysis; Style critique
• CPC Class Codes: G06F 40/289 Phrasal analysis, e.g. finite state techniques or chunking
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06Q 30/0209 Incentive being awarded or redeemed in connection with the playing of a video game
• CPC Class Codes: G07F 17/3244 Payment aspects of a gaming system, e.g. payment schemes, setting payout ratio, bonus or consolation prizes
• CPC Class Codes: H04L 51/04 Real-time or near real-time messaging, e.g. instant messaging [IM]
• CPC Class Codes: H04M 1/72436 for text messaging, e.g. short messaging services [SMS] or e-mails
• CPC Class Codes: H04W 4/18 Information format or content conversion, e.g. adaptation by the network of the transmitted or received information for the purpose of wireless delivery to users or terminals

Abstract

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.

Claims

1. A computer-implemented method comprising using one or more computers to perform operations comprising:

selecting first text from a text field in proximity to a current position of an input cursor in the text field, the first text comprising at least one of a word, a sentence fragment, a sentence, a phrase, or a passage that precedes or follows the current position of the input cursor;

performing sentiment analysis to determine a first sentiment of the first text in the text field, the first sentiment relating to a user'"'"'s attitude with respect to a topic described in the first text;

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,

wherein performing sentiment analysis comprises locating and analyzing subjective information in the first text using at least one of statistics, computational linguistics, and natural language processing.

2. The method of claim 1, further comprising:

determining that the first text is text associated with a brand, a product, or a service and, based thereon, identifying a candidate emoticon for the brand, the product, or the service.

3. The method of claim 1, further comprising:

calculating the score of a particular candidate emoticon based on a distance between the first and second texts, a historical number of user selections of the particular emoticon, and similarity between the first and second sentiment.

4. The method of claim 1 wherein the score is further based on similarity between a natural language of the first text and a natural language of the second text.

5. The method of claim 1, wherein providing the candidate emoticons comprises presenting the candidate emoticons for user selection at or near the current position of the input cursor.

6. The method of claim 1, wherein identifying the candidate emoticons is further based on at least a preference of the user, user-related information, or recipient-related information.

7. The method of claim 1, further comprising:

providing an application programming interface through which the identifying of the candidate emoticons can be initiated.

8. The method of claim 1, wherein performing sentiment analysis comprises associating at least one term in the first text with a numerical value on a scale comprising a range of polarity from negative to positive.

9. The method of claim 1, wherein performing sentiment analysis comprises using at least one classifier selected from the group consisting of Max Entropy and support vector machines.

10. The method of claim 1, wherein performing sentiment analysis comprises reviewing the first text in real-time, as the first text is being entered into the text field.

11. The method of claim 1, wherein performing sentiment analysis comprises ignoring an objective portion of the first text.

12. The method of claim 1, further comprising:

receiving one or more user-defined emoticons provided by a user, each user-defined emoticon comprising a visual representation of the emoticon and being associated with a respective natural language and respective text.

13. The method of claim 12, further comprising providing statistics to the user pertaining to use of the user-defined emoticons by other users.

14. The method of claim 12, further comprising:

crediting an account of the user for creation of the user-defined emoticons.

15. The method of claim 14 wherein the credit is a virtual asset for an electronic game.

16. A system comprising:

a searchable corpus of emoticons; and

one or more computers programmed to provide an application programming interface which is configured to perform operations comprising;

selecting first text from a text field in proximity to a current position of an input cursor in the text field, the first text comprising at least one of a word, a sentence fragment, a sentence, a phrase, or a passage that precedes or follows the current position of the input cursor;

performing sentiment analysis to determine a first sentiment of the first text in the text field, the first sentiment relating to a user'"'"'s attitude with respect to a topic described in the first text;

identifying one or more candidate emoticons in the corpus 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 of 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,

wherein performing sentiment analysis comprises locating and analyzing subjective information in the first text using at least one of statistics, computational linguistics, and natural language processing.

17. The system of claim 16, the operations further comprising:

determining that the first text is text associated with a brand, a product, or a service and, based thereon, identifying a candidate emoticon for the brand, the product, or the service.

18. The system of claim 16, the operations further comprising:

calculating the score of a particular candidate emoticon based on a distance between the first and second texts, a historical number of user selections of the particular emoticon, and similarity between the first and second sentiment.

19. The system of claim 16 wherein the score is further based on similarity between a natural language of the first text and a natural language of the second text.

20. The system of claim 16, wherein identifying the candidate emoticons is further based on at least a preference of the user, user-related information, or recipient-related information.

21. The system of claim 16, the operations further comprising:

providing an application programming interface through which the identifying of the candidate emoticons can be initiated.

22. The system of claim 16, wherein performing sentiment analysis comprises associating at least one term in the first text with a numerical value on a scale comprising a range of polarity from negative to positive.

23. The system of claim 16, wherein performing sentiment analysis comprises using at least one classifier selected from the group consisting of Max Entropy and support vector machines.

24. The system of claim 16, wherein performing sentiment analysis comprises reviewing the first text in real-time, as the first text is being entered into the text field.

25. The system of claim 16, wherein performing sentiment analysis comprises ignoring an objective portion of the first text.

26. The system of claim 16, the operations further comprising:

receiving one or more user-defined emoticons provided by a user, each user-defined emoticon comprising a visual representation of the emoticon and being associated with a respective natural language and respective text.

27. The system of claim 26, the operations further comprising providing statistics to the user pertaining to use of the user-defined emoticons by other users.

28. The system of claim 26, the operations further comprising:

crediting an account of the user for creation of the user-defined emoticons.

29. The system of claim 28 wherein the credit is a virtual asset for an electronic game.

30. A computer program product stored in one or more non-transitory storage media for controlling a processing mode of a data processing apparatus, the computer program product being executable by the data processing apparatus to cause the data processing apparatus to perform operations comprising:

selecting first text from a text field in proximity to a current position of an input cursor in the text field, the first text comprising at least one of a word, a sentence fragment, a sentence, a phrase, or a passage that precedes or follows the current position of the input cursor;

performing sentiment analysis to determine a first sentiment of the first text in the text field, the first sentiment relating to a user'"'"'s attitude with respect to a topic described in the first text;

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,

wherein performing sentiment analysis comprises locating and analyzing subjective information in the first text using at least one of statistics, computational linguistics, and natural language processing.