186,011 research outputs found
Weak ties: Subtle role of information diffusion in online social networks
As a social media, online social networks play a vital role in the social
information diffusion. However, due to its unique complexity, the mechanism of
the diffusion in online social networks is different from the ones in other
types of networks and remains unclear to us. Meanwhile, few works have been
done to reveal the coupled dynamics of both the structure and the diffusion of
online social networks. To this end, in this paper, we propose a model to
investigate how the structure is coupled with the diffusion in online social
networks from the view of weak ties. Through numerical experiments on
large-scale online social networks, we find that in contrast to some previous
research results, selecting weak ties preferentially to republish cannot make
the information diffuse quickly, while random selection can achieve this goal.
However, when we remove the weak ties gradually, the coverage of the
information will drop sharply even in the case of random selection. We also
give a reasonable explanation for this by extra analysis and experiments.
Finally, we conclude that weak ties play a subtle role in the information
diffusion in online social networks. On one hand, they act as bridges to
connect isolated local communities together and break through the local
trapping of the information. On the other hand, selecting them as preferential
paths to republish cannot help the information spread further in the network.
As a result, weak ties might be of use in the control of the virus spread and
the private information diffusion in real-world applications.Comment: Final version published in PR
Contrasting Multiple Social Network Autocorrelations for Binary Outcomes, With Applications To Technology Adoption
The rise of socially targeted marketing suggests that decisions made by
consumers can be predicted not only from their personal tastes and
characteristics, but also from the decisions of people who are close to them in
their networks. One obstacle to consider is that there may be several different
measures for "closeness" that are appropriate, either through different types
of friendships, or different functions of distance on one kind of friendship,
where only a subset of these networks may actually be relevant. Another is that
these decisions are often binary and more difficult to model with conventional
approaches, both conceptually and computationally. To address these issues, we
present a hierarchical model for individual binary outcomes that uses and
extends the machinery of the auto-probit method for binary data. We demonstrate
the behavior of the parameters estimated by the multiple network-regime
auto-probit model (m-NAP) under various sensitivity conditions, such as the
impact of the prior distribution and the nature of the structure of the
network, and demonstrate on several examples of correlated binary data in
networks of interest to Information Systems, including the adoption of Caller
Ring-Back Tones, whose use is governed by direct connection but explained by
additional network topologies
On the Effect of Semantically Enriched Context Models on Software Modularization
Many of the existing approaches for program comprehension rely on the
linguistic information found in source code, such as identifier names and
comments. Semantic clustering is one such technique for modularization of the
system that relies on the informal semantics of the program, encoded in the
vocabulary used in the source code. Treating the source code as a collection of
tokens loses the semantic information embedded within the identifiers. We try
to overcome this problem by introducing context models for source code
identifiers to obtain a semantic kernel, which can be used for both deriving
the topics that run through the system as well as their clustering. In the
first model, we abstract an identifier to its type representation and build on
this notion of context to construct contextual vector representation of the
source code. The second notion of context is defined based on the flow of data
between identifiers to represent a module as a dependency graph where the nodes
correspond to identifiers and the edges represent the data dependencies between
pairs of identifiers. We have applied our approach to 10 medium-sized open
source Java projects, and show that by introducing contexts for identifiers,
the quality of the modularization of the software systems is improved. Both of
the context models give results that are superior to the plain vector
representation of documents. In some cases, the authoritativeness of
decompositions is improved by 67%. Furthermore, a more detailed evaluation of
our approach on JEdit, an open source editor, demonstrates that inferred topics
through performing topic analysis on the contextual representations are more
meaningful compared to the plain representation of the documents. The proposed
approach in introducing a context model for source code identifiers paves the
way for building tools that support developers in program comprehension tasks
such as application and domain concept location, software modularization and
topic analysis
Diffusion on Complex Networks : A way to probe their large scale topological structures
A diffusion process on complex networks is introduced in order to uncover
their large scale topological structures. This is achieved by focusing on the
slowest decaying diffusive modes of the network. The proposed procedure is
applied to real-world networks like a friendship network of known modular
structure, and an Internet routing network. For the friendship network, its
known structure is well reproduced. In case of the Internet, where the
structure is far less well-known, one indeed finds a modular structure, and
modules can roughly be associated with individual countries. Quantitatively the
modular structure of the Internet manifests itself in an approximately 10 times
larger participation ratio of its slowest decaying modes as compared to the
null model -- a random scale-free network. The extreme edges of the Internet
are found to correspond to Russian and US military sites.Comment: Latex, 13 pages, 4 figures (To appear Physica A
Modelling and simulation framework for reactive transport of organic contaminants in bed-sediments using a pure java object - oriented paradigm
Numerical modelling and simulation of organic contaminant reactive transport in the environment is being increasingly
relied upon for a wide range of tasks associated with risk-based decision-making, such as prediction of contaminant
profiles, optimisation of remediation methods, and monitoring of changes resulting from an implemented remediation
scheme. The lack of integration of multiple mechanistic models to a single modelling framework, however, has
prevented the field of reactive transport modelling in bed-sediments from developing a cohesive understanding of
contaminant fate and behaviour in the aquatic sediment environment. This paper will investigate the problems involved
in the model integration process, discuss modelling and software development approaches, and present preliminary
results from use of CORETRANS, a predictive modelling framework that simulates 1-dimensional organic contaminant
reaction and transport in bed-sediments
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
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