1. A system used in a computing environment in which unstructured computer text is analyzed for theme generation to determine sentiment, the system comprising: a computer store including unstructured text that is delimited, a searched phrases log, and a phrase click log, the unstructured text being input via a web page, input directly into the computer store via a first computer file, or any combination thereof, the searched phrases log comprising a) a unique set of phrases from all phrases that are searched on one or more specified websites for a specified duration and b) a search phrase frequency count indicating the number of times of the phrases within the unique set of phrases was searched on the one or more specified websites over the specified duration, the searched phrases log being i) retrieved from the internet and stored in the computer store via a second computer file, ii) input directly into the computer store via a third computer file, or any combination of i) and ii), and the phrase click log comprising a) a unique set of phrases from all phrases that correspond to one or more Uniform Resource Locators (URLs) that are activated for a specified duration and b) a clicked-on frequency count indicating the number of times of the URLs associated with the phrases in the unique set of phrases are activated over the specified duration, the phrase click log is i) retrieved from the internet and stored in the computer store via a fourth computer file, ii) input via a webpage, input directly into the computer store via a fifth computer file, or any combination of i) and ii), and a computer server in communication with the computer store and programmed to: extract phrases from the unstructured delimited text by splitting each line of the unstructured delimited text into one or more phrases; generate tokens from the unstructured delimited text, wherein the tokens comprise segments of the unstructured delimited text; determine one or more themes present in the unstructured delimited text by: a) identifying candidate phrases based on the tokens and the searched phrases log, b) ranking each of the candidate phrases based on frequency of a respective phrase in the unstructured delimited text, the search phrase frequency count corresponding to the respective phrase, and the clicked-on frequency count corresponding to the respective phrase, c) selecting a subset of phrases from the candidate phrases, where the subset of phrases selected is based on the respective rank of each phrase, d) grouping the subset of phrases based on words in the subset of phrases, and e) determining themes for each grouping based on the number of times a phrase appears in the group.