The Social Amplifier-Reaction of Human Communities to Emergencies

Yaniv Altshuler, Michael Fire, Erez Shmueli, Yuval Elovici, Alfred Bruckstein, Alex (Sandy) Pentland, David Lazer

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


This paper develops a methodology to aggregate signals in a network regarding some hidden state of the world. We argue that focusing on edges around hubs will under certain circumstances amplify the faint signals disseminating in a network, allowing for more efficient detection of that hidden state. We apply this method to detecting emergencies in mobile phone data, demonstrating that under a broad range of cases and a constraint in how many edges can be observed at a time, focusing on the egocentric networks around key hubs will be more effective than sampling random edges. We support this conclusion analytically, through simulations, and with analysis of a dataset containing the call log data from a major mobile carrier in a European nation.

Original languageEnglish
Pages (from-to)399-418
Number of pages20
JournalJournal of Statistical Physics
Issue number3
StatePublished - 1 Aug 2013


  • Mobile phone networks
  • Network science

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics


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