58,371 research outputs found
Spreading processes in Multilayer Networks
Several systems can be modeled as sets of interconnected networks or networks
with multiple types of connections, here generally called multilayer networks.
Spreading processes such as information propagation among users of an online
social networks, or the diffusion of pathogens among individuals through their
contact network, are fundamental phenomena occurring in these networks.
However, while information diffusion in single networks has received
considerable attention from various disciplines for over a decade, spreading
processes in multilayer networks is still a young research area presenting many
challenging research issues. In this paper we review the main models, results
and applications of multilayer spreading processes and discuss some promising
research directions.Comment: 21 pages, 3 figures, 4 table
Competition and dual users in complex contagion processes
We study the competition of two spreading entities, for example innovations,
in complex contagion processes in complex networks. We develop an analytical
framework and examine the role of dual users, i.e. agents using both
technologies. Searching for the spreading transition of the new innovation and
the extinction transition of a preexisting one, we identify different phases
depending on network mean degree, prevalence of preexisting technology, and
thresholds of the contagion process. Competition with the preexisting
technology effectively suppresses the spread of the new innovation, but it also
allows for phases of coexistence. The existence of dual users largely modifies
the transient dynamics creating new phases that promote the spread of a new
innovation and extinction of a preexisting one. It enables the global spread of
the new innovation even if the old one has the first-mover advantage.Comment: 9 pages, 4 figure
Knowledge transfer in a tourism destination: the effects of a network structure
Tourism destinations have a necessity to innovate to remain competitive in an
increasingly global environment. A pre-requisite for innovation is the
understanding of how destinations source, share and use knowledge. This
conceptual paper examines the nature of networks and how their analysis can
shed light upon the processes of knowledge sharing in destinations as they
strive to innovate. The paper conceptualizes destinations as networks of
connected organizations, both public and private, each of which can be
considered as a destination stakeholder. In network theory they represent the
nodes within the system. The paper shows how epidemic diffusion models can act
as an analogy for knowledge communication and transfer within a destination
network. These models can be combined with other approaches to network analysis
to shed light on how destination networks operate, and how they can be
optimized with policy intervention to deliver innovative and competitive
destinations. The paper closes with a practical tourism example taken from the
Italian destination of Elba. Using numerical simulations the case demonstrates
how the Elba network can be optimized. Overall this paper demonstrates the
considerable utility of network analysis for tourism in delivering destination
competitiveness.Comment: 15 pages, 2 figures, 2 tables. Forthcoming in: The Service Industries
Journal, vol. 30, n. 8, 2010. Special Issue on: Advances in service network
analysis v2: addeded and corrected reference
Accelerating Scientific Discovery by Formulating Grand Scientific Challenges
One important question for science and society is how to best promote
scientific progress. Inspired by the great success of Hilbert's famous set of
problems, the FuturICT project tries to stimulate and focus the efforts of many
scientists by formulating Grand Challenges, i.e. a set of fundamental, relevant
and hardly solvable scientific questions.Comment: To appear in EPJ Special Topics. For related work see
http://www.futurict.eu and http://www.soms.ethz.c
Competition and Success in the Meme Pool: a Case Study on Quickmeme.com
The advent of social media has provided data and insights about how people
relate to information and culture. While information is composed by bits and
its fundamental building bricks are relatively well understood, the same cannot
be said for culture. The fundamental cultural unit has been defined as a
"meme". Memes are defined in literature as specific fundamental cultural
traits, that are floating in their environment together. Just like genes
carried by bodies, memes are carried by cultural manifestations like songs,
buildings or pictures. Memes are studied in their competition for being
successfully passed from one generation of minds to another, in different ways.
In this paper we choose an empirical approach to the study of memes. We
downloaded data about memes from a well-known website hosting hundreds of
different memes and thousands of their implementations. From this data, we
empirically describe the behavior of these memes. We statistically describe
meme occurrences in our dataset and we delineate their fundamental traits,
along with those traits that make them more or less apt to be successful
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