@article{palla2007quantifying,
  author = {Palla, Gergely and Barabási, Albert-lászló and Vicsek, Tamás and Hungary, Budapest},
  interhash = {911359764769215213b2d31dc6394078},
  intrahash = {9c5a50822cb5580b66a7371b833bb2fe},
  pages = 2007,
  title = {Quantifying social group evolution},
  url = {http://130.203.133.150/viewdoc/summary?doi=10.1.1.119.7541},
  volume = 446,
  year = 2007
}

@article{barabsi2013network,
  abstract = {Professor Barabási's talk described how the tools of network science can help understand the Web's structure, development and weaknesses. The Web is an information network, in which the nodes are documents (at the time of writing over one trillion of them), connected by links. Other well-known network structures include the Internet, a physical network where the nodes are routers and the links are physical connections, and organizations, where the nodes are people and the links represent communications.},
  author = {Barabási, Albert-László},
  doi = {10.1098/rsta.2012.0375},
  eprint = {http://rsta.royalsocietypublishing.org/content/371/1987/20120375.full.pdf+html},
  interhash = {e2cfdd2e3c7c68581e3ab691909ed28b},
  intrahash = {208c1f9d6d8eff67cee07ebdf3cd0fc1},
  journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
  number = 1987,
  title = {Network science},
  url = {http://rsta.royalsocietypublishing.org/content/371/1987/20120375.abstract},
  volume = 371,
  year = 2013
}

@article{vazquez2006modeling,
  abstract = { The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. Here we provide direct evidence that for five human activity patterns, such as email and letter based communications, web browsing, library visits and stock trading, the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. We show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experiencing very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. We discuss two queuing models that capture human activity. The first model assumes that there are no limitations on the number of tasks an individual can hadle at any time, predicting that the waiting time of the individual tasks follow a heavy tailed distribution P(τw)∼τw−α with α=3∕2. The second model imposes limitations on the queue length, resulting in a heavy tailed waiting time distribution characterized by α=1. We provide empirical evidence supporting the relevance of these two models to human activity patterns, showing that while emails, web browsing and library visitation display α=1, the surface mail based communication belongs to the α=3∕2 universality class. Finally, we discuss possible extension of the proposed queuing models and outline some future challenges in exploring the statistical mechanics of human dynamics.},
  author = {Vázquez, Alexei and Gama Oliveira, João and Dezsö, Zoltán and Goh, Kwang-Il and Kondor, Imre and Barabási, Albert-László},
  doi = {10.1103/PhysRevE.73.036127},
  interhash = {679487e36d59d3d8262632b9a05f9f45},
  intrahash = {f15dafcb20d0c9857acf1324c5c2279c},
  journal = {Physical Review E},
  month = mar,
  number = 3,
  numpages = {19},
  pages = 036127,
  publisher = {American Physical Society},
  title = {Modeling bursts and heavy tails in human dynamics},
  url = {http://link.aps.org/doi/10.1103/PhysRevE.73.036127},
  volume = 73,
  year = 2006
}

@article{Song19022010,
  abstract = {A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual’s trajectory, we find a 93% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.},
  author = {Song, Chaoming and Qu, Zehui and Blumm, Nicholas and Barabási, Albert-László},
  doi = {10.1126/science.1177170},
  eprint = {http://www.sciencemag.org/content/327/5968/1018.full.pdf},
  interhash = {f2611a08bf6db54f86e884c05f3cb5fb},
  intrahash = {a89330f8eb32ce62b5f5c9a2b4909f25},
  journal = {Science},
  number = 5968,
  pages = {1018-1021},
  title = {Limits of Predictability in Human Mobility},
  url = {http://www.sciencemag.org/content/327/5968/1018.abstract},
  volume = 327,
  year = 2010
}

@article{song2010limits,
  abstract = {A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual's trajectory, we find a 93% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.},
  author = {Song, Chaoming and Qu, Zehui and Blumm, Nicholas and Barabási, Albert-László},
  doi = {10.1126/science.1177170},
  eprint = {http://www.sciencemag.org/cgi/reprint/327/5968/1018.pdf},
  interhash = {f2611a08bf6db54f86e884c05f3cb5fb},
  intrahash = {a89330f8eb32ce62b5f5c9a2b4909f25},
  journal = {Science},
  number = 5968,
  pages = {1018--1021},
  title = {Limits of Predictability in Human Mobility},
  url = {http://www.barabasilab.com/pubs/CCNR-ALB_Publications/201002-19_Science-Predictability/201002-19_Science-Predictability.pdf},
  volume = 327,
  year = 2010
}

@article{song2010limits,
  abstract = {A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual's trajectory, we find a 93% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.
},
  author = {Song, Chaoming and Qu, Zehui and Blumm, Nicholas and Barabási, Albert-László},
  doi = {10.1126/science.1177170},
  eprint = {http://www.sciencemag.org/cgi/reprint/327/5968/1018.pdf},
  interhash = {f2611a08bf6db54f86e884c05f3cb5fb},
  intrahash = {a89330f8eb32ce62b5f5c9a2b4909f25},
  journal = {Science},
  number = 5968,
  pages = {1018--1021},
  title = {Limits of Predictability in Human Mobility},
  url = {http://www.barabasilab.com/pubs/CCNR-ALB_Publications/201002-19_Science-Predictability/201002-19_Science-Predictability.pdf},
  volume = 327,
  year = 2010
}

@article{song2010limits,
  abstract = {A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual's trajectory, we find a 93% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.
},
  author = {Song, Chaoming and Qu, Zehui and Blumm, Nicholas and Barabási, Albert-László},
  doi = {10.1126/science.1177170},
  eprint = {http://www.sciencemag.org/cgi/reprint/327/5968/1018.pdf},
  interhash = {f2611a08bf6db54f86e884c05f3cb5fb},
  intrahash = {a89330f8eb32ce62b5f5c9a2b4909f25},
  journal = {Science},
  number = 5968,
  pages = {1018--1021},
  title = {Limits of Predictability in Human Mobility},
  url = {http://www.sciencemag.org/cgi/content/abstract/327/5968/1018},
  volume = 327,
  year = 2010
}

@article{barabasi99emergence,
  author = {Barabási, Albert-László and Albert, Réka},
  interhash = {a09e31f3baed5f4d2112ad182621f269},
  intrahash = {73f0eae7189f539854c5d59bae595942},
  journal = {Science},
  pages = {509--512},
  title = {Emergence of scaling in random networks},
  volume = 286,
  year = 1999
}

@article{albert:02statistical,
  author = {Albert, Reka and Barabasi, Albert-Laszlo},
  eid = {47},
  interhash = {a35a2b3e25194fdaa4e569fa4447bb9d},
  intrahash = {1161e1dc8cfd785d62fb509b9604b14d},
  journal = {Reviews of Modern Physics},
  number = 1,
  numpages = {51},
  pages = 47,
  publisher = {APS},
  title = {Statistical mechanics of complex networks},
  url = {http://link.aps.org/abstract/RMP/v74/p47},
  volume = 74,
  year = 2002
}