Quantifying the Digital Traces of Hurricane Sandy on Flickr

Society’s increasing interactions with technology are creating extensive “digital traces” of our collective human behavior. These new data sources are fuelling the rapid development of the new field of computational social science. To investigate user attention to the Hurricane Sandy disaster in 2012, we analyze data from Flickr, a popular website for sharing personal photographs. In this case study, we find that the number of photos taken and subsequently uploaded to Flickr with titles, descriptions or tags related to Hurricane Sandy bears a striking correlation to the atmospheric pressure in the US state New Jersey during this period. Appropriate leverage of such information could be useful to policy makers and others charged with emergency crisis management.

[1]  Mike Thelwall,et al.  General patterns of tag usage among university groups in Flickr , 2008, Online Inf. Rev..

[2]  Brian Tivnan,et al.  Pattern in Escalations in Insurgent and Terrorist Activity , 2011, Science.

[3]  Lada A. Adamic,et al.  Computational Social Science , 2009, Science.

[4]  Nick Chater,et al.  Using big data to predict collective behavior in the real world 1 , 2014, Behavioral and Brain Sciences.

[5]  H. Eugene Stanley,et al.  Quantifying Wikipedia Usage Patterns Before Stock Market Moves , 2013, Scientific Reports.

[6]  Acknowledgments , 2006, Molecular and Cellular Endocrinology.

[7]  D. Helbing,et al.  Quantifying the Behavior of Stock Correlations Under Market Stress , 2012, Scientific Reports.

[8]  A. Vespignani.  Predicting the Behavior of Techno-Social Systems , 2009, Science.

[9]  Andrew M. Cox.  Flickr: a case study of Web2.0 , 2008, Aslib Proc..

[10]  Michael F. Goodchild,et al.  Please Scroll down for Article International Journal of Digital Earth Crowdsourcing Geographic Information for Disaster Response: a Research Frontier Crowdsourcing Geographic Information for Disaster Response: a Research Frontier , 2022 .

[11]  John Ziman,et al.  At the research frontier , 1977 .

[12]  H. Stanley,et al.  Quantifying Trading Behavior in Financial Markets Using Google Trends , 2013, Scientific Reports.

[13]  Ingmar Weber,et al.  Camera Brand Congruence and Camera Model Propagation in the Flickr Social Graph , 2011, TWEB.

[14]  H Eugene Stanley,et al.  Complex dynamics of our economic life on different scales: insights from search engine query data , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[15]  M. Batty.  The Size, Scale, and Shape of Cities , 2008, Science.

[16]  Sergey V. Buldyrev,et al.  Correlated randomness and switching phenomena , 2010 .

[17]  Jeremy Ginsberg,et al.  Detecting influenza epidemics using search engine query data , 2009, Nature.

[18]  H. Stanley,et al.  Switching processes in financial markets , 2011, Proceedings of the National Academy of Sciences.

[19]  H. Eugene Stanley,et al.  Quantifying the Advantage of Looking Forward , 2012, Scientific Reports.

[20]  Pauline Rafferty,et al.  Flickr and Democratic Indexing: dialogic approaches to indexing , 2007, Aslib Proc..

[21]  H. Stanley,et al.  Linking agent-based models and stochastic models of financial markets , 2012, Proceedings of the National Academy of Sciences.

[22]  J. Nadal,et al.  Manifesto of computational social science , 2012 .