1. A computer-implemented method for determining sentiment in Web documents, the method comprising: harvesting one or more Web documents from one or more content sources and extracting keywords from the Web documents; filtering, at a server, the keywords according to a phase transition method to produce filtered keywords; determining one or more categories for the Web documents according to the filtered keywords; determining sentiment expressed in the Web documents on a category-by-category basis; the sentiment determined by analysis of words identified as sentiment-bearing or opinion-bearing within the web documents; and reporting the sentiment so determined; wherein prior to extracting the keywords, harvested Web documents are filtered to remove Web documents which are not candidates for containing sentiment-bearing content, the filtering of the Web documents including, for each candidate Web document, extracting n-grams, determining an n-gram spectrum for the candidate Web document based on the extracted n-grams, wherein the n-gram spectrum indicates a frequency of occurrence of n-grams as a function of a size of n-grams, and determining whether the n-gram spectrum for the candidate document conforms to a reference n-gram spectrum within a predetermined threshold, wherein the reference n-gram spectrum is defined by a predetermined function; and wherein the predetermined function is cx −a ·e −bx , where x is the size of the n-gram, and a, b, and c are predetermined values that place a peak of the predetermined function between an n-gram of size 2 and an n-gram of size 3.
1. A computer-implemented method for determining sentiment in Web documents, the method comprising: harvesting one or more Web documents from one or more content sources and extracting keywords from the Web documents; filtering, at a server, the keywords according to a phase transition method to produce filtered keywords; determining one or more categories for the Web documents according to the filtered keywords; determining sentiment expressed in the Web documents on a category-by-category basis; the sentiment determined by analysis of words identified as sentiment-bearing or opinion-bearing within the web documents; and reporting the sentiment so determined; wherein prior to extracting the keywords, harvested Web documents are filtered to remove Web documents which are not candidates for containing sentiment-bearing content, the filtering of the Web documents including, for each candidate Web document, extracting n-grams, determining an n-gram spectrum for the candidate Web document based on the extracted n-grams, wherein the n-gram spectrum indicates a frequency of occurrence of n-grams as a function of a size of n-grams, and determining whether the n-gram spectrum for the candidate document conforms to a reference n-gram spectrum within a predetermined threshold, wherein the reference n-gram spectrum is defined by a predetermined function; and wherein the predetermined function is cx −a ·e −bx , where x is the size of the n-gram, and a, b, and c are predetermined values that place a peak of the predetermined function between an n-gram of size 2 and an n-gram of size 3. 13. The computer-implemented method of claim 1 , wherein determining sentiment comprises determining polarities of individual sentences, or portions thereof, in respective ones of the Web documents.