38 research outputs found
Human dynamics revealed through Web analytics
When the World Wide Web was first conceived as a way to facilitate the
sharing of scientific information at the CERN (European Center for Nuclear
Research) few could have imagined the role it would come to play in the
following decades. Since then, the increasing ubiquity of Internet access and
the frequency with which people interact with it raise the possibility of using
the Web to better observe, understand, and monitor several aspects of human
social behavior. Web sites with large numbers of frequently returning users are
ideal for this task. If these sites belong to companies or universities, their
usage patterns can furnish information about the working habits of entire
populations. In this work, we analyze the properly anonymized logs detailing
the access history to Emory University's Web site. Emory is a medium size
university located in Atlanta, Georgia. We find interesting structure in the
activity patterns of the domain and study in a systematic way the main forces
behind the dynamics of the traffic. In particular, we show that both linear
preferential linking and priority based queuing are essential ingredients to
understand the way users navigate the Web.Comment: 7 pages, 8 figure
Towards the characterization of individual users through Web analytics
We perform an analysis of the way individual users navigate in the Web. We
focus primarily in the temporal patterns of they return to a given page. The
return probability as a function of time as well as the distribution of time
intervals between consecutive visits are measured and found to be independent
of the level of activity of single users. The results indicate a rich variety
of individual behaviors and seem to preclude the possibility of defining a
characteristic frequency for each user in his/her visits to a single site.Comment: 8 pages, 4 figures. To appear in Proceeding of Complex'0
Seasonality in Dynamic Stochastic Block Models
Sociotechnological and geospatial processes exhibit time varying structure
that make insight discovery challenging. This paper proposes a new statistical
model for such systems, modeled as dynamic networks, to address this challenge.
It assumes that vertices fall into one of k types and that the probability of
edge formation at a particular time depends on the types of the incident nodes
and the current time. The time dependencies are driven by unique seasonal
processes, which many systems exhibit (e.g., predictable spikes in geospatial
or web traffic each day). The paper defines the model as a generative process
and an inference procedure to recover the seasonal processes from data when
they are unknown. Evaluation with synthetic dynamic networks show the recovery
of the latent seasonal processes that drive its formation.Comment: 4 page worksho
New activity pattern in human interactive dynamics
We investigate the response function of human agents as demonstrated by
written correspondence, uncovering a new universal pattern for how the reactive
dynamics of individuals is distributed across the set of each agent's contacts.
In long-term empirical data on email, we find that the set of response times
considered separately for the messages to each different correspondent of a
given writer, generate a family of heavy-tailed distributions, which have
largely the same features for all agents, and whose characteristic times grow
exponentially with the rank of each correspondent. We furthermore show that
this universal behavioral pattern emerges robustly by considering weighted
moving averages of the priority-conditioned response-time probabilities
generated by a basic prioritization model. Our findings clarify how the range
of priorities in the inputs from one's environment underpin and shape the
dynamics of agents embedded in a net of reactive relations. These newly
revealed activity patterns might be present in other general interactive
environments, and constrain future models of communication and interaction
networks, affecting their architecture and evolution.Comment: 15 pages, 7 figure