1. A method performed by one or more server devices, the method comprising: storing, by a processor associated with the one or more server devices, a user profile that includes an author likelihood score of a particular user, the author likelihood score estimating a likelihood that the particular user will become an author of comments; receiving, by a processor associated with the one or more server devices and from users, one or more explicit requests for comments for a particular document, the one or more explicit requests for comments being associated with the users selecting a visual object to request comments about the particular document when the particular document is a document without comments; receiving, by a processor associated with the one or more server devices, an indication that the particular user has accessed flail the particular document; determining, by a processor associated with the one or more server devices, that the particular document has been identified as needing comments when a quantity of the one or more explicit requests for comments, received for the particular document, exceeds a threshold; retrieving, by a processor associated with the one or more server devices and from the user profile, the author likelihood score for the particular user, based on determining that the particular document has been identified as needing comments; determining, by a processor associated with the one or more server devices, whether the retrieved author likelihood score is greater than a particular threshold; and providing, by a processor associated with the one or more server devices, a suggestion to the particular user to write a comment about the particular document, based on: determining that the retrieved author likelihood score is greater than the particular threshold, and determining that the particular document has been identified as needing comments.
1. A method performed by one or more server devices, the method comprising: storing, by a processor associated with the one or more server devices, a user profile that includes an author likelihood score of a particular user, the author likelihood score estimating a likelihood that the particular user will become an author of comments; receiving, by a processor associated with the one or more server devices and from users, one or more explicit requests for comments for a particular document, the one or more explicit requests for comments being associated with the users selecting a visual object to request comments about the particular document when the particular document is a document without comments; receiving, by a processor associated with the one or more server devices, an indication that the particular user has accessed flail the particular document; determining, by a processor associated with the one or more server devices, that the particular document has been identified as needing comments when a quantity of the one or more explicit requests for comments, received for the particular document, exceeds a threshold; retrieving, by a processor associated with the one or more server devices and from the user profile, the author likelihood score for the particular user, based on determining that the particular document has been identified as needing comments; determining, by a processor associated with the one or more server devices, whether the retrieved author likelihood score is greater than a particular threshold; and providing, by a processor associated with the one or more server devices, a suggestion to the particular user to write a comment about the particular document, based on: determining that the retrieved author likelihood score is greater than the particular threshold, and determining that the particular document has been identified as needing comments. 5. The method of claim 1 , further comprising: identifying the particular document as a document without comments, where the particular document is associated with at least a particular rank score with respect to a particular topic; and identifying the particular document as needing comments based on: identifying the document as a document without comments, and the particular document being associated with at least the particular rank score with respect to the particular topic.