2017/03/21 by James P. Bagrow, Bagrow, James P.
Computer Science · Physics and Astronomy · Social Sciences · #Anomaly detection #Complex Network Analysis Techniques #Computer science #Computer security #Computers and Society (cs.CY) #Crash #Data Analysis #Data mining #Data science #Event (particle physics) #Extant taxon #FOS: Computer and information sciences #FOS: Physical sciences #Human Mobility and Location-Based Analysis #Mobile phone #Opinion Dynamics and Social Influence #Phone #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #Social media #Statistics and Probability (physics.data-an) #Telecommunications #World Wide Web #cs.CY #cs.SI #physics.data-an #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1703.07362
published in arXiv (Cornell University) (Cornell University) · 19 pages, 11 figures
arxiv created 2017/03/21 · openalex publication_date 2017/03/21 · arxiv updated 2017/03/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
The most critical time for information to spread is in the aftermath of a serious emergency, crisis, or disaster. Individuals affected by such situations can now turn to an array of communication channels, from mobile phone calls and text messages to social media posts, when alerting social ties. These channels drastically improve the speed of information in a time-sensitive event, and provide extant records of human dynamics during and afterward the event. Retrospective analysis of such anomalous events provides researchers with a class of "found experiments" that may be used to better understand social spreading. In this chapter, we study information spreading due to a number of emergency events, including the Boston Marathon Bombing and a plane crash at a western European airport. We also contrast the different information which may be gleaned by social media data compared with mobile phone data and we estimate the rate of anomalous events in a mobile phone dataset using a proposed anomaly detection method.