Abstract: A method finds patterns in a target real-valued time series by utilizing sentiment and frequency derived from a stream of social media messages, wherein the target represents a quantifiable property of an asset being tracked. The method includes identifying a target, which is a sampled real-valued time series; generating a sentiment time series, ss, relating to an asset; generating a frequency time series, sf, relating to an asset; and determining a pattern based upon the sentiment time series and the frequency time series.