Systems and methods for identifying and suggesting 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 computer-implemented method comprising:
receiving first text submitted by a first user;
for each of a plurality of different previously submitted texts, calculating a text similarity score based on a textual similarity of the first text to the previously submitted text, and calculating a sentiment similarity score based on a similarity between sentiment of the first text and sentiment of the previously submitted text;
based on the scores, selecting one or more of the previously submitted texts having closest similarity to the first text;
for each of the selected texts, identifying an emoticon previously selected by a user for insertion into the selected text; and
providing the identified emoticons for selection by the first user.
2. The method of claim 1 , further comprising:
receiving selection by the first user of one of the identified emoticons; and
inserting the selected emoticon into the first text.
3. The method of claim 2 , wherein the selected emoticon is inserted at a current position of an input cursor in the first text.
4. The method of claim 1 wherein selecting one or more of the previously submitted texts having closest similarity to the first text comprises:
generating a combined score for each of the previously submitted texts based on a combination of similarity scores calculated for the previously submitted text; and
selecting one or more of the previously submitted texts based on the combined scores.
5. The method of claim 4 wherein the combination of similarity scores is a weighted combination.
6. The method of claim 1 wherein calculating the text similarity score between a particular previously submitted text and the first text comprises calculating an edit distance between the particular text and the first text.
7. The method of claim 1 wherein calculating the text similarity score between a particular previously submitted text and the first text comprises determining if a plurality of words in the particular text occur in the first text in the same order that they occur in the particular text.
8. The method of claim 1 , further comprising:
calculating a language similarity score based on a similarity between a language of the first text and a language of a second text.
9. The method of claim 1 wherein a particular identified emoticon is a user-defined emoticon comprising a visual representation and being associated with a respective sentiment.
10. A system comprising:
one or more computers programmed to perform operations comprising:
receiving first text submitted by a first user;
for each of a plurality of different previously submitted texts, calculating a text similarity score based on a textual similarity of the first text to the previously submitted text, and calculating a sentiment similarity score based on a similarity between sentiment of the first text and sentiment of the previously submitted text;
based on the scores, selecting one or more of the previously submitted texts having closest similarity to the first text;
for each of the selected texts, identifying an emoticon previously selected by a user for insertion into the selected text; and
providing the identified emoticons for selection by the first user.
11. The system of claim 10 wherein the operations further comprise:
receiving selection by the first user of one of the identified emoticons; and
inserting the selected emoticon into the first text.
12. The system of claim 11 , wherein the selected emoticon is inserted at a current position of an input cursor in the first text.
13. The system of claim 10 wherein selecting one or more of the previously submitted texts having closest similarity to the first text comprises:
generating a combined score for each of the previously submitted texts based on a combination of similarity scores calculated for the previously submitted text; and
selecting one or more of the previously submitted texts based on the combined scores.
14. The system of claim 13 wherein the combination of similarity scores is a weighted combination.
15. The system of claim 10 wherein calculating the text similarity score between a particular previously submitted text and the first text comprises calculating an edit distance between the particular text and the first text.
16. The system of claim 10 wherein calculating the text similarity score between a particular previously submitted text and the first text comprises determining if a plurality of words in the particular text occur in the first text in the same order that they occur in the particular text.
17. The system of claim 10 wherein the operations further comprise:
calculating a language similarity score based on a similarity between a language of the first text and a language of a second text.
18. The system of claim 10 wherein a particular identified emoticon is a user-defined emoticon comprising a visual representation and being associated with a respective sentiment.
19. An article comprising a non-transitory machine-readable medium having instructions stored thereon that when executed by a computer causes the computer to perform operations comprising:
receiving first text submitted by a first user;
for each of a plurality of different previously submitted texts, calculating a text similarity score based on a textual similarity of the first text to the previously submitted text, and calculating a sentiment similarity score based on a similarity between sentiment of the first text and sentiment of the previously submitted text;
based on the scores, selecting one or more of the previously submitted texts having closest similarity to the first text;
for each of the selected texts, identifying an emoticon previously selected by a user for insertion into the selected text; and
providing the identified emoticons for selection by the first user.
20. The article of claim 19 wherein the operations further comprise:
receiving selection by the first user of one of the identified emoticons; and
inserting the selected emoticon into the first text.
21. The article of claim 20 , wherein the selected emoticon is inserted at a current position of an input cursor in the first text.
22. The article of claim 19 wherein selecting one or more of the previously submitted texts having closest similarity to the first text comprises:
generating a combined score for each of the previously submitted texts based on a combination of similarity scores calculated for the previously submitted text; and
selecting one or more of the previously submitted texts based on the combined scores.
23. The article of claim 22 wherein the combination of similarity scores is a weighted combination.
24. The article of claim 19 wherein calculating the text similarity score between a particular previously submitted text and the first text comprises calculating an edit distance between the particular text and the first text.
25. The article of claim 19 wherein calculating the text similarity score between a particular previously submitted text and the first text comprises determining if a plurality of words in the particular text occur in the first text in the same order that they occur in the particular text.
26. The article of claim 19 wherein the operations further comprise:
calculating a language similarity score based on a similarity between a language of the first text and a language of a second text.