1. A method for classifying comments on an idea submission, comprising: receiving a collection of textual comments from users, each of the comments in the collection comprising text in a natural language and annotating an idea submission, previously-submitted by another user, which includes a description of an idea; for each of a plurality of comment classes, providing at least one pattern for assigning a textual comment to the class based on the occurrence of a specified syntactic relation in the comment, the comment classes including: a first class for reaction to the content of the idea, a second class for expression of a commenter's judgment of an idea's value, and a third class for reaction to an idea generation process in which the associated idea submission is made, the at least one pattern for the third class comprising a pattern which identifies when a term in the comment which is in a set of terms designated as being associated with a domain-specific PROCESS concept is present in a comment sentence; natural language processing each of the comments to identify dependencies in at least a part of the comment; based on the identified dependencies, automatically classifying the comments according to the plurality of comment classes, the classifying including applying the at least one pattern for identifying comments that are assigned to the third comment class; wherein when the comment is assigned to the first class, the method further includes proposing appending at least a part of the comment to the description of the associated idea submission; wherein when the comment is assigned to the second class, the method further includes providing for rating the idea submission; and outputting information based on the assigned comment classes, wherein the natural language processing, classifying, and outputting are performed with a computer processor.
1. A method for classifying comments on an idea submission, comprising: receiving a collection of textual comments from users, each of the comments in the collection comprising text in a natural language and annotating an idea submission, previously-submitted by another user, which includes a description of an idea; for each of a plurality of comment classes, providing at least one pattern for assigning a textual comment to the class based on the occurrence of a specified syntactic relation in the comment, the comment classes including: a first class for reaction to the content of the idea, a second class for expression of a commenter's judgment of an idea's value, and a third class for reaction to an idea generation process in which the associated idea submission is made, the at least one pattern for the third class comprising a pattern which identifies when a term in the comment which is in a set of terms designated as being associated with a domain-specific PROCESS concept is present in a comment sentence; natural language processing each of the comments to identify dependencies in at least a part of the comment; based on the identified dependencies, automatically classifying the comments according to the plurality of comment classes, the classifying including applying the at least one pattern for identifying comments that are assigned to the third comment class; wherein when the comment is assigned to the first class, the method further includes proposing appending at least a part of the comment to the description of the associated idea submission; wherein when the comment is assigned to the second class, the method further includes providing for rating the idea submission; and outputting information based on the assigned comment classes, wherein the natural language processing, classifying, and outputting are performed with a computer processor. 9. The method of claim 1 , wherein the classification comprises accessing a vocabulary comprising, for each of a set of domain dependent concepts, a respective set of terms, and for each of a set of domain independent concepts, a respective set of terms and applying patterns for classifying the comments including patterns which each specify at least one of the domain dependent and domain-independent concepts.