Large-Scale Sentiment Analysis for News and Blogs (system demonstration)

News can be good or bad, but it is seldom neutral. Although full comprehension of natural language text remains well beyond the power of machines, the statistical analysis of relatively simple sentiment cues can provide a surprisingly meaningful sense of how the latest news impacts important entities. Here we demonstrate our large-scale sentiment analysis system for news and blog entities built on top of the Lydia text analysis system [1]. We determine the public sentiment on each of the hundreds of thousands of entities that we track, and how this sentiment varies with time. We encourage the reader to study our historical sentiment analysis for your favorite news entities at http://www.textmap.com and view daily sentiment at http://www.textmap.com/sentiment. The results of our sentiment analysis correlate very well with historical events: