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Books > Computing & IT > Social & legal aspects of computing
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Exploratory Analysis in Dynamic Social Networks - Theoretical and Practical Applications (Paperback)
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Exploratory Analysis in Dynamic Social Networks - Theoretical and Practical Applications (Paperback)
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Social interactions within networks comprise an increasing event
nowadays. Different aspects of societies and competitive markets,
such as Social Medias through the Internet and Telecommunications
environments hold a high correlation with the social network
analysis methodology. By understanding these social structures and
its interactions might be possible to realize how individuals and
consumers relate each other and hence predict further social
structures in the future. However, most of the current social
network analysis projects are in relation to static structures, not
considering how the social network evolves over the time. The
dynamic approach can points out new perspectives in terms of social
network analysis, including prediction and simulations scenarios.
In order to perceive the social network relations over the time is
crucial to collect the distinct snapshots of the social structure,
understanding not just how the social members relate each other but
in addition to that how this relationships evolves over the time.
Measures in relation to social network describe nodes and links by
static metrics, depicting its strength, its overall distances to
the other related nodes, and its amounts of connections, among
others. This dynamic approach makes possible to create a historical
data, quite usual for predictive modeling. As such, new social
network measures and algorithms should be created in order to
describe dynamic features assigned to social structures over the
time. Chapter 1 gives a brief overview of social network, such as
its characteristics and how to visualize it. Chapter 2 discusses
the general practice of building pervasive online social networks
using real-world services and presents various projects that focus
on the online social networking of the physical world. Chapter 3
presents a semantic model, non probabilistic and predictive, for
the decisional analysis of professional and institutional social
networks. Chapter 4 describes a novel approach towards the
visualization and analysis of network dynamics. The goal is to
handle network data and visualization in ways that explicitly deal
with its time-based nature while simultaneously assessing nodal-
and macro- network dynamics. Chapter 5 shows how the network
topology affects epidemic diffusion and cascade dynamics. It also
clarifies the largest maximum eigenvalue of the adjacency matrix of
the network is the key index to estimate the properties of
networks. Chapter 6, discusses the behaviors of malware propagation
in online social networks using analytical models and conducts some
simulations. Chapter 7 analyzes the Google Analytics data from
multiple web companies. These web services all positioned
themselves as social network sites within a relatively short time
from their establishment. Several important measures available on
Google Analytics were discussed with experienced practitioners to
be identified for data collection. Chapter 8 explores the effects
of spatiality and the direction of information transmission over
cooperation dynamics. The model is based on the well-known "selfish
herd" concept, and assumes that cultural and biological dynamics
are driven by natural selection of the phenotypes. This model
allows us to study the differences between the dynamics of
cooperative, group-forming individuals subject to a selective
pressure (predation). Chapter 9 does the survey about the types of
private information and privacy threats on social network graphs,
and then introduce the methods to protect the private information.
Chapter 10 reviews the e-Government development processes in
Canada, Malaysia, Australia, Singapore and Korea in order to
identify the factors that contribute to the successful development
of e-Government therein.
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