Abstract
The vast amount of written text available on the Internet provides a treasure trove of information for intelligence and security analysts, but only if the useful data can be quickly identified among all the irrelevant information. Many analytical tools available provide information about the sentiment of written texts; however, these tools typically utilize only one measure of sentiment in their metrics. Rosoka Software leverages psycholinguistic research across multiple sentiment vectors to provide precise information about an author’s language and pinpoint documents that do not follow predicted patterns. Rosoka’s multi-vector sentiment analysis uses four metrics to help analysts identify outliers in their data, recognize heightened emotional language, sort data by media type, and subset large data sets into only the documents that require further assessment. Read Full Text Here