Socioeconomic Tracker using Unconventional Data

Modern economies and societies produce massive datasets that need to be analysed using new modelling techniques. In particular, measuring the informational content of text in economic and social news is useful for market participants and societies to adjust their perception and expectations on the dynamics of future events and trends, thus significantly influencing policy-makers’ perception and decisions. Social media and news may provide a larger set of information than standard lower frequency socio-economic indicators. This dataset collects various unconventional datasets extracted from news and social media (Data from Google Trends (https://trends.google.com/), JRC computations) which have the potential of bringing together insights on different socio-economic trends.