Authors: Manuel Garcia-Herranz, Esteban Moro, Manuel Cebrian, Nicholas A. Christakis and James H. Fowler
Journal: PLoS ONE 9(4): e92413 (2014) LINK
SummaryRecent research has focused on the monitoring of global–scale online data for improved detection of epidemics, mood patterns, movements in the stock market political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly- articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a friend of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, but also more effective, and it may be applied to monitor contagious processes in global–scale networks.
* The science of going viral, [The Chronicle of Higher Education](http://chronicle.com/blogs/percolator/the-science-of-going-viral/34145) * How to Use Twitter Friends as Sensors to Detect Disease Outbreaks, [Technology Review MIT](http://www.technologyreview.com/view/508091/how-to-use-twitter-friends-as-sensors-to-detect-disease-outbreaks/) * Going viral: How 'social contagion' begins and escalates, [Bloomberg Businessweek](http://investing.businessweek.com/research/markets/news/article.asp?docKey=600-201404101313M2______EUPR_____7af500000170ad87_3600-1) * Nice summary of our work at the [Robert Wood Johnson Foundation](http://www.rwjf.org/en/research-publications/find-rwjf-research/2014/04/using-friends-as-sensors-to-detect-global-scale-contagious-outbr.html) webpage * How 'social contagion' begins and escalates, [PhysOrg](http://phys.org/news/2014-04-social-contagion-escalates.html) * System detects global trends in social networks two months in advance, [ScienceDaily](http://www.sciencedaily.com/releases/2014/04/140428094211.htm) * Tus tuits predicen el futuro, [Huffington Post](http://www.huffingtonpost.es/2014/04/29/twitter-predice-el-futuro_n_5231224.html) * Predicting contagious outbreaks using your most popular friends [FastCompany.com](http://www.fastcoexist.com/3029058/predicting-contagious-outbreaks-using-your-most-popular-friends) * The Case for Journeying to the Center of Our Social Networks, [RWJF.com](http://www.rwjf.org/en/blogs/pioneering-ideas/2014/05/the_case_for_journey.html?cid=xtw_pioneer)