293 research outputs found
Information spreading during emergencies and anomalous events
The most critical time for information to spread is in the aftermath of a
serious emergency, crisis, or disaster. Individuals affected by such situations
can now turn to an array of communication channels, from mobile phone calls and
text messages to social media posts, when alerting social ties. These channels
drastically improve the speed of information in a time-sensitive event, and
provide extant records of human dynamics during and afterward the event.
Retrospective analysis of such anomalous events provides researchers with a
class of "found experiments" that may be used to better understand social
spreading. In this chapter, we study information spreading due to a number of
emergency events, including the Boston Marathon Bombing and a plane crash at a
western European airport. We also contrast the different information which may
be gleaned by social media data compared with mobile phone data and we estimate
the rate of anomalous events in a mobile phone dataset using a proposed anomaly
detection method.Comment: 19 pages, 11 figure
On the Google-Fame of Scientists and Other Populations
We study the fame distribution of scientists and other social groups as
measured by the number of Google hits garnered by individuals in the
population. Past studies have found that the fame distribution decays either in
power-law [arXiv:cond-mat/0310049] or exponential [Europhys. Lett., 67, (4)
511-516 (2004)] fashion, depending on whether individuals in the social group
in question enjoy true fame or not. In our present study we examine critically
Google counts as well as the methods of data analysis. While the previous
findings are corroborated in our present study, we find that, in most
situations, the data available does not allow for sharp conclusions.Comment: 6 pages, 1 figure, to appear in the proceedings of the 8th Granada
seminar on Computational Physic
Investigating Bimodal Clustering in Human Mobility
We apply a simple clustering algorithm to a large dataset of cellular
telecommunication records, reducing the complexity of mobile phone users' full
trajectories and allowing for simple statistics to characterize their
properties. For the case of two clusters, we quantify how clustered human
mobility is, how much of a user's spatial dispersion is due to motion between
clusters, and how spatially and temporally separated clusters are from one
another.Comment: 4 pages, 2 figure
Link communities reveal multiscale complexity in networks
Networks have become a key approach to understanding systems of interacting
objects, unifying the study of diverse phenomena including biological organisms
and human society. One crucial step when studying the structure and dynamics of
networks is to identify communities: groups of related nodes that correspond to
functional subunits such as protein complexes or social spheres. Communities in
networks often overlap such that nodes simultaneously belong to several groups.
Meanwhile, many networks are known to possess hierarchical organization, where
communities are recursively grouped into a hierarchical structure. However, the
fact that many real networks have communities with pervasive overlap, where
each and every node belongs to more than one group, has the consequence that a
global hierarchy of nodes cannot capture the relationships between overlapping
groups. Here we reinvent communities as groups of links rather than nodes and
show that this unorthodox approach successfully reconciles the antagonistic
organizing principles of overlapping communities and hierarchy. In contrast to
the existing literature, which has entirely focused on grouping nodes, link
communities naturally incorporate overlap while revealing hierarchical
organization. We find relevant link communities in many networks, including
major biological networks such as protein-protein interaction and metabolic
networks, and show that a large social network contains hierarchically
organized community structures spanning inner-city to regional scales while
maintaining pervasive overlap. Our results imply that link communities are
fundamental building blocks that reveal overlap and hierarchical organization
in networks to be two aspects of the same phenomenon.Comment: Main text and supplementary informatio
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