The Social Amplifier—Reaction of Human Communities to Emergencies
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....
| Auteurs principaux: | , , , , , , |
|---|---|
| Autres auteurs: | |
| Format: | Article |
| Langue: | en_US |
| Publié: |
Springer-Verlag
2014
|
| Accès en ligne: | http://hdl.handle.net/1721.1/85200 https://orcid.org/0000-0002-8053-9983 https://orcid.org/0000-0002-0346-2994 https://orcid.org/0000-0002-3410-9587 |
| Résumé: | 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. |
|---|