News Analytics

News Analytics

News analysis refers to the measurement of the various qualitative and quantitative attributes of textual (unstructured data) news stories. Some of these attributes are: sentiment, relevance, and novelty. Expressing news stories as numbers permits the manipulation of everyday information in a mathematical and statistical way.

News analytics are used in financial modeling, particularly in quantitative and algorithmic trading. Further, news analytics can be used to plot and characterize firm behaviors over time and thus yield important strategic insights about rival firms.

News analytics are usually derived through automated text analysis and applied to digital texts using elements from natural language processing and machine learning such as latent semantic analysis, support vector machines, "bag of words" among other techniques.