What if computers could read the news?
We monitor the news to learn about the changes in the world. However, every working day millions of news articles are published and any many more news messages are found in social media. How can we handle this massive bombardment of information, while our world is becoming more and more global and connected? How can we avoid being selective and biased in our view of the world?
We develop computer programs that read these massive streams of daily news across 4 languages (English, Dutch, Spanish and Italian) to extract what happened, when and where, and who is involved. By recording the changes day-by-day, we build up a knowledge store that records the history over longer spans of time. Our technology interprets natural language text to build up a formal representation of these changes over which computers can reason. You can ask the computer to provide the history of individual persons, companies, places and regions, find connections, derive social networks, detect trends and long-term developments of all types of events. So far, we could only measure how much news there is on a day. Now, we can start ask ourselves the question how much the world changed yesterday according to the news.
We processed hundreds of thousands articles on various topics related to the financial and economic domain, coming from thousands of different sources. This reveals many stories that took place during the financial-economic crisis in the last ten years but it also shows how these sources differ from each other: who tells what part of the story, where do sources disagree or differ. Likewise, we not only can learn about the changes in the world but also about the media that report on it.