  Synchronising a database of stock specific news with 5 years worth of order
book data on 300 stocks, we show that abnormal price movements following news
releases (exogenous) exhibit markedly different dynamical features from those
arising spontaneously (endogenous). On average, large volatility fluctuations
induced by exogenous events occur abruptly and are followed by a decaying
power-law relaxation, while endogenous price jumps are characterized by
progressively accelerating growth of volatility, also followed by a power-law
relaxation, but slower than for exogenous jumps. Remarkably, our results are
reminiscent of what is observed in different contexts, namely Amazon book sales
and YouTube views. Finally, we show that fitting power-laws to {\it individual}
volatility profiles allows one to classify large events into endogenous and
exogenous dynamical classes, without relying on the news feed.
