1. A computer implemented method of assessing human sentiment from a group of documents, each document in the group of documents having a plurality of terms and being digitally represented in a computer, said method comprising: receiving a group of documents, each document in the group of documents comprising a context of a plurality of terms and all documents in the group of documents representative of a particular topic; constructing a document sentiment vector space from the group of documents, wherein construction of the document sentiment vector space comprises: assessing sentimentality of each document in the group of documents toward the topic; identifying sentimentally significant documents in the group of documents with heightened sentimentality toward the particular topic; and labeling sentimentally significant documents by including a unique sentiment binding term in the context of the plurality of terms; representing each document in the group of documents in the document sentiment vector space; defining a region of sentimental significance in the document sentiment vector space based on an occurrence of document representations for sentimentally significant documents with the unique sentiment binding term; receiving a query string; and assessing sentimentality of the query string by comparing a representation of the query string for semantic similarity to the region of sentimental significance in the document sentiment vector space.