Sentiment-based classification of media content

1. A computer-implemented method, comprising:

identifying, at a server, a plurality of comments associated with a content item;

generating, for each of the plurality of comments, a plurality of sentiment scores for each sentiment from a plurality of sentiments by applying a sentiment classifier for each sentiment of the plurality of sentiments, wherein a value of the sentiment score for each sentiment indicates a likelihood of a corresponding comment being associated with that sentiment; and

causing a sentiment to be presented for the plurality of comments associated with the content item based on the plurality of sentiment scores.

2. The computer-implemented method of claim 1 , further comprising storing, for each comment of the plurality of comments, the plurality of sentiment scores.

3. The computer-implemented method of claim 1 , further comprising:

receiving, from a user device, a request to present information associated with the plurality of sentiment scores associated with the plurality of comments; and

in response to receiving the request, causing a subset of the plurality of sentiment scores associated with a corresponding subset of the plurality of comments to be presented by the user device.

4. The computer-implemented method of claim 1 , wherein the request is a request that indicates one or more sentiments from the plurality of sentiments.

5. The computer-implemented method of claim 1 , wherein each sentiment score of the plurality of sentiment scores is a continuous value.

6. The computer-implemented method of claim 1 , wherein the request is a request that indicates a sentiment from the plurality of sentiments.

7. The computer-implemented method of claim 1 , wherein the plurality of comments includes at least one thread of comments, wherein the thread of comments includes a parent comment and at least one reply to the parent comment.

8. The computer-implemented method of claim 1 , wherein each comment in the plurality of comments is associated with a value that indicates a number of users that agree with the comment.

9. The computer-implemented method of claim 1 , wherein the plurality of comments associated with the content item is assigned a label indicating a type of the sentiment expressed in the plurality of comments.

10. The computer-implemented method of claim 1 , wherein the plurality of comments associated with the content item is assigned a label indicating a magnitude of the sentiment expressed in the plurality of comments.

11. A computer-implemented system, comprising:

a hardware processor that:

identifies a plurality of comments associated with a content item;

generates, for each of the plurality of comments, a plurality of sentiment scores for each sentiment from a plurality of sentiments by applying a sentiment classifier for each sentiment of the plurality of sentiments, wherein a value of the sentiment score for each sentiment indicates a likelihood of a corresponding comment being associated with that sentiment; and

causes a sentiment to be presented for the plurality of comments associated with the content item based on the plurality of sentiment scores.

12. The computer-implemented system of claim 11 , wherein the hardware processor further stores, for each comment of the plurality of comments, the plurality of sentiment scores.

13. The computer-implemented system of claim 11 , herein the hardware processor further:

receives, from a user device, a request to present information associated with the plurality of sentiment scores associated with the plurality of comments; and

in response to receiving the request, causes a subset of the plurality of sentiment scores associated with a corresponding subset of the plurality of comments to be presented by the user device.

14. The computer-implemented system of claim 11 , wherein the request is a request that indicates one or more sentiments from the plurality of sentiments.

15. The computer-implemented system of claim 11 , wherein each sentiment score of the plurality of sentiment scores is a continuous value.

16. The computer-implemented system of claim 11 , wherein the request is a request that indicates a sentiment from the plurality of sentiments.

17. The computer-implemented system of claim 11 , wherein the plurality of comments includes at least one thread of comments, wherein the thread of comments includes a parent comment and at least one reply to the parent comment.

18. The computer-implemented system of claim 11 , wherein each comment in the plurality of comments is associated with a value that indicates a number of users that agree with the comment.

19. The computer-implemented system of claim 11 , wherein the plurality of comments associated with the content item is assigned a label indicating a type of the sentiment expressed in the plurality of comments.

20. The computer-implemented system of claim 11 , wherein the plurality of comments associated with the content item is assigned a label indicating a magnitude of the sentiment expressed in the plurality of comments.

21. A non-transitory computer-readable medium containing computer executable instructions that, when executed by a processor, cause the processor to perform a method, the method comprising:

identifying, at a server, a plurality of comments associated with a content item;

generating, for each of the plurality of comments, a plurality of sentiment scores for each sentiment from a plurality of sentiments by applying a sentiment classifier for each sentiment of the plurality of sentiments, wherein a value of the sentiment score for each sentiment indicates a likelihood of a corresponding comment being associated with that sentiment; and

causing a sentiment to be presented for the plurality of comments associated with the content item based on the plurality of sentiment scores.