PUMA publications for /author/Imre%20Kondorhttps://puma.uni-kassel.de/author/Imre%20KondorPUMA RSS feed for /author/Imre%20Kondor2024-03-28T20:44:20+01:00Modeling bursts and heavy tails in human dynamicshttps://puma.uni-kassel.de/bibtex/2f15dafcb20d0c9857acf1324c5c2279c/jaeschkejaeschke2011-10-04T10:23:38+02:00dynamics social analysis network sna <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexei Vázquez" itemprop="url" href="/author/Alexei%20V%c3%a1zquez"><span itemprop="name">A. Vázquez</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="João Gama Oliveira" itemprop="url" href="/author/Jo%c3%a3o%20Gama%20Oliveira"><span itemprop="name">J. Gama Oliveira</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Zoltán Dezsö" itemprop="url" href="/author/Zolt%c3%a1n%20Dezs%c3%b6"><span itemprop="name">Z. Dezsö</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Kwang-Il Goh" itemprop="url" href="/author/Kwang-Il%20Goh"><span itemprop="name">K. Goh</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Imre Kondor" itemprop="url" href="/author/Imre%20Kondor"><span itemprop="name">I. Kondor</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Albert-László Barabási" itemprop="url" href="/author/Albert-L%c3%a1szl%c3%b3%20Barab%c3%a1si"><span itemprop="name">A. Barabási</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>Physical Review E</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">73 </span></span>(<span itemprop="issueNumber">3</span>):
<span itemprop="pagination">036127</span></em> </span>(<em><span>März 2006<meta content="März 2006" itemprop="datePublished"/></span></em>)Tue Oct 04 10:23:38 CEST 2011Physical Review Emar3036127Modeling bursts and heavy tails in human dynamics732006dynamics social analysis network sna 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.Diffusion Kernels on Graphs and Other Discrete Input Spaceshttps://puma.uni-kassel.de/bibtex/23a49cc3c52a3f5fe1474f822b3f973b0/hothohotho2007-06-14T15:36:47+02:00graphs kernels toread <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Risi Imre Kondor" itemprop="url" href="/author/Risi%20Imre%20Kondor"><span itemprop="name">R. Kondor</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="John D. Lafferty" itemprop="url" href="/author/John%20D.%20Lafferty"><span itemprop="name">J. Lafferty</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">ICML '02: Proceedings of the Nineteenth International Conference on Machine Learning</span>, </em></span><em>Seite <span itemprop="pagination">315--322</span>. </em><em>San Francisco, CA, USA, </em><em><span itemprop="publisher">Morgan Kaufmann Publishers Inc.</span>, </em>(<em><span>2002<meta content="2002" itemprop="datePublished"/></span></em>)Thu Jun 14 15:36:47 CEST 2007San Francisco, CA, USAICML '02: Proceedings of the Nineteenth International Conference on Machine Learning315--322Diffusion Kernels on Graphs and Other Discrete Input Spaces2002graphs kernels toread