Lockheed Martin Corporation / Crane / IBM / Twitter / YouTube / U.S. Army Research Laboratory / /
Country
United States / China / /
Event
Business Partnership / Reorganization / /
Facility
Institute of Computing Technology / Northeastern University / University of Miami / U.S. Army Research Laboratory / /
IndustryTerm
citation networks / web users / large social networks / online media / online popularity / risk management / social network / heterogeneous bibliographic networks / online content / implict networks / /
Organization
National Natural Science Foundation of China / Chinese Academy of Sciences / American Physical Society / Association for the Advancement of Artificial Copyright / United States Army / Northeastern University / Boston / Beijing Natural Science Foundation / European Commission / Defence Advanced Research Projects Agency / Physical Society / Institute of Computing Technology / Department of Physics / Network Science Collaborative Technology Alliance / University of Miami / Center for Complex Network Research / /
Person
Coral Gables / /
Position
Hunter / RPP model for later discussions / /
Product
Eqs / /
ProvinceOrState
Florida / New York / Massachusetts / Arkansas / /
PublishedMedium
PLoS ONE / Reviews of Modern Physics / Communications of the ACM / Physical Review / Physical Review Letters / /
Modeling and Predicting Popularity Dynamics via Reinforced Poisson Processes Huawei Shen1 , Dashun Wang2 , Chaoming Song3 , Albert-L´aszl´o Barab´asi4 1 Institute of Computing Technology, Chinese Academy of Sciences,