10. The computer-readable non-transitory storage media of claim 9 wherein said highlight specific words within said web page based on said topic model, further comprises: extracting content of said newly selected web page; determining a probability score for each of said plurality of topics in said topic model for how well said each of said plurality of topics describes said content; selecting a set of said plurality of topics that meet a predefined criteria analyzing said content utilizing said set of topics; determining a weight for each of a plurality of keywords associated with said set of topics, wherein different weights are determined for different keywords among said plurality of keywords depending how significant said each of said plurality of keywords are determined to be; and differentially highlighting said plurality of keywords associated with said set of topics within said content of said newly selected web page according to said weight.
10. The computer-readable non-transitory storage media of claim 9 wherein said highlight specific words within said web page based on said topic model, further comprises: extracting content of said newly selected web page; determining a probability score for each of said plurality of topics in said topic model for how well said each of said plurality of topics describes said content; selecting a set of said plurality of topics that meet a predefined criteria analyzing said content utilizing said set of topics; determining a weight for each of a plurality of keywords associated with said set of topics, wherein different weights are determined for different keywords among said plurality of keywords depending how significant said each of said plurality of keywords are determined to be; and differentially highlighting said plurality of keywords associated with said set of topics within said content of said newly selected web page according to said weight. 12. The computer-readable non-transitory storage media of claim 10 wherein said evaluate said content from said newly selected web page for keywords associated with said subset of topics and which represent significant trends across said subset of topics, further comprises utilizing natural language processing to map different forms of said keywords and synonyms to specific stem-words within said topic model.