56,347 research outputs found
A Relational Event Approach to Modeling Behavioral Dynamics
This chapter provides an introduction to the analysis of relational event
data (i.e., actions, interactions, or other events involving multiple actors
that occur over time) within the R/statnet platform. We begin by reviewing the
basics of relational event modeling, with an emphasis on models with piecewise
constant hazards. We then discuss estimation for dyadic and more general
relational event models using the relevent package, with an emphasis on
hands-on applications of the methods and interpretation of results. Statnet is
a collection of packages for the R statistical computing system that supports
the representation, manipulation, visualization, modeling, simulation, and
analysis of relational data. Statnet packages are contributed by a team of
volunteer developers, and are made freely available under the GNU Public
License. These packages are written for the R statistical computing
environment, and can be used with any computing platform that supports R
(including Windows, Linux, and Mac).
A network-based view of regional growth
The need to better understand the mechanisms underlying regional growth patterns is widely recognised. This paper argues that regional growth is partly a function of the value created through inter-organisational flows of knowledge within and across regions. It is proposed that investment in calculative networks by organisations to access knowledge is a form of capital, termed network capital, which should be incorporated into regional growth models. The paper seeks to develop a framework to capture the value of network capital within these models based on the spatial configuration and the nature of the knowledge flowing through networks
Timing interactions in social simulations: The voter model
The recent availability of huge high resolution datasets on human activities
has revealed the heavy-tailed nature of the interevent time distributions. In
social simulations of interacting agents the standard approach has been to use
Poisson processes to update the state of the agents, which gives rise to very
homogeneous activity patterns with a well defined characteristic interevent
time. As a paradigmatic opinion model we investigate the voter model and review
the standard update rules and propose two new update rules which are able to
account for heterogeneous activity patterns. For the new update rules each node
gets updated with a probability that depends on the time since the last event
of the node, where an event can be an update attempt (exogenous update) or a
change of state (endogenous update). We find that both update rules can give
rise to power law interevent time distributions, although the endogenous one
more robustly. Apart from that for the exogenous update rule and the standard
update rules the voter model does not reach consensus in the infinite size
limit, while for the endogenous update there exist a coarsening process that
drives the system toward consensus configurations.Comment: Book Chapter, 23 pages, 9 figures, 5 table
Discourse network analysis: policy debates as dynamic networks
Political discourse is the verbal interaction between political actors. Political actors make normative claims about policies conditional on each other. This renders discourse a dynamic network phenomenon. Accordingly, the structure and dynamics of policy debates can be analyzed with a combination of content analysis and dynamic network analysis. After annotating statements of actors in text sources, networks can be created from these structured data, such as congruence or conflict networks at the actor or concept level, affiliation networks of actors and concept stances, and longitudinal versions of these networks. The resulting network data reveal important properties of a debate, such as the structure of advocacy coalitions or discourse coalitions, polarization and consensus formation, and underlying endogenous processes like popularity, reciprocity, or social balance. The added value of discourse network analysis over survey-based policy network research is that policy processes can be analyzed from a longitudinal perspective. Inferential techniques for understanding the micro-level processes governing political discourse are being developed
Economic Geography and the Evolution of Networks
An evolutionary perspective on economic geography requires a dynamic understanding of change in networks. This paper explores theories of network evolution for their use in geography and develops the conceptual framework of geographical network trajectories. It specifically assesses how tie selection constitutes the evolutionary process of retention and variation in network structure and how geography affects these mechanisms. Finally, a typology of regional network formations is used to discuss opportunities for innovation in and across regions.evolution, network trajectory, evolutionary economic geography, social network analysis, innovation
Niche as a determinant of word fate in online groups
Patterns of word use both reflect and influence a myriad of human activities
and interactions. Like other entities that are reproduced and evolve, words
rise or decline depending upon a complex interplay between {their intrinsic
properties and the environments in which they function}. Using Internet
discussion communities as model systems, we define the concept of a word niche
as the relationship between the word and the characteristic features of the
environments in which it is used. We develop a method to quantify two important
aspects of the size of the word niche: the range of individuals using the word
and the range of topics it is used to discuss. Controlling for word frequency,
we show that these aspects of the word niche are strong determinants of changes
in word frequency. Previous studies have already indicated that word frequency
itself is a correlate of word success at historical time scales. Our analysis
of changes in word frequencies over time reveals that the relative sizes of
word niches are far more important than word frequencies in the dynamics of the
entire vocabulary at shorter time scales, as the language adapts to new
concepts and social groupings. We also distinguish endogenous versus exogenous
factors as additional contributors to the fates of words, and demonstrate the
force of this distinction in the rise of novel words. Our results indicate that
short-term nonstationarity in word statistics is strongly driven by individual
proclivities, including inclinations to provide novel information and to
project a distinctive social identity.Comment: Supporting Information is available here:
http://www.plosone.org/article/fetchSingleRepresentation.action?uri=info:doi/10.1371/journal.pone.0019009.s00
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