1. A computer implemented text processing system for analyzing sentiment information related to a topic having a plurality of subtopics, comprising: a text clustering component that clusters sub-document linguistic units of a plurality of relevant documents into separate clusters based on the subject matter of the linguistic units such that each cluster includes linguistic units from one or more of the relevant documents each of which is related to one of the plurality of subtopics; a sentiment analyzer that attributes a sentiment to the linguistic units, wherein the sentiment analyzer also attributes a confidence measure objectively indicative of a confidence with which the sentiment is assigned to the linguistic units; a report generator that identifies linguistic units and generates a report based on the clusters and based on the sentiment attributed to the linguistic units related to the subtopic of each cluster; wherein the sentiment analyzer is trained using a machine learning process based on features extracted from training data, and wherein the features used in training the sentiment analyzer are removed from use in the text clustering component such that the features used in training the sentiment analyzer are excluded from being a basis upon which the text clustering component performs said step of clustering the sub-document linguistic units of the plurality of relevant documents; a display component displaying data indicative of the clusters, wherein the display includes an adjustable user input mechanism that receives a user-selection of a desired minimum sentiment confidence level that each linguistic unit must exceed to be included in any of the clusters, and wherein the text clustering component excludes at least one particular of said linguistic units from one of said separate clusters based on a determination that the confidence measure attributed to the particular linguistic unit by the sentiment analyzer is less than the desired minimum sentiment confidence level selected by the user by way of the adjustable user input mechanism; and a computer processor that is a component of the computer, wherein the computer processor implements the text clustering component such that the computer processor performs said step of clustering sub-document linguistic units of a plurality of relevant documents into separate clusters based on the subject matter of the linguistic units.
1. A computer implemented text processing system for analyzing sentiment information related to a topic having a plurality of subtopics, comprising: a text clustering component that clusters sub-document linguistic units of a plurality of relevant documents into separate clusters based on the subject matter of the linguistic units such that each cluster includes linguistic units from one or more of the relevant documents each of which is related to one of the plurality of subtopics; a sentiment analyzer that attributes a sentiment to the linguistic units, wherein the sentiment analyzer also attributes a confidence measure objectively indicative of a confidence with which the sentiment is assigned to the linguistic units; a report generator that identifies linguistic units and generates a report based on the clusters and based on the sentiment attributed to the linguistic units related to the subtopic of each cluster; wherein the sentiment analyzer is trained using a machine learning process based on features extracted from training data, and wherein the features used in training the sentiment analyzer are removed from use in the text clustering component such that the features used in training the sentiment analyzer are excluded from being a basis upon which the text clustering component performs said step of clustering the sub-document linguistic units of the plurality of relevant documents; a display component displaying data indicative of the clusters, wherein the display includes an adjustable user input mechanism that receives a user-selection of a desired minimum sentiment confidence level that each linguistic unit must exceed to be included in any of the clusters, and wherein the text clustering component excludes at least one particular of said linguistic units from one of said separate clusters based on a determination that the confidence measure attributed to the particular linguistic unit by the sentiment analyzer is less than the desired minimum sentiment confidence level selected by the user by way of the adjustable user input mechanism; and a computer processor that is a component of the computer, wherein the computer processor implements the text clustering component such that the computer processor performs said step of clustering sub-document linguistic units of a plurality of relevant documents into separate clusters based on the subject matter of the linguistic units. 11. The text processing system of claim 1 wherein the text clustering component comprises a subject matter clustering component that clusters the linguistic units based on predefined subject matter.