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Using empirical data from a social media site (Twitter) and on tradingvolumes of financial securities, we analyze the correlated human activity inmassive social organizations. The activity, typically excited by real-worldevents and measured by the occurrence rate of international brand names andtrading volumes, is characterized by intermittent fluctuations with bursts ofhigh activity separated by quiescent periods. These fluctuations are broadlydistributed with an inverse cubic tail and have long-range temporalcorrelations with a $1/f$ power spectrum. We describe the activity by astochastic point process and derive the distribution of activity levels fromthe corresponding stochastic differential equation. The distribution and thecorresponding power spectrum are fully consistent with the empiricalobservations.

Excitable human dynamics driven by extrinsic events in massive communities