Abstract: Typically, virtual communities exhibit the well-known
phenomenon of participation inequality, which means that only a
small percentage of users is responsible of the majority of
contributions. However, the sustainability of the community requires
that the group of active users must be continuously nurtured with new
users that gain expertise through a participation process. This paper
analyzes the time evolution of Open Source Software (OSS)
communities, considering users that join/abandon the community
over time and several topological properties of the network when
modeled as a social network. More specifically, the paper analyzes
the role of those users rejoining the community and their influence in
the global characteristics of the network.
Abstract: In a multi-cultural learning context, where ties are
weak and dynamic, combining qualitative with quantitative research
methods may be more effective. Such a combination may also allow
us to answer different types of question, such as about people’s
perception of the network. In this study the use of observation,
interviews and photos were explored as ways of enhancing data from
social network questionnaires. Integrating all of these methods was
found to enhance the quality of data collected and its accuracy, also
providing a richer story of the network dynamics and the factors that
shaped these changes over time.
Abstract: Electronic Word-Of-Mouth (eWOM) communities
represent today an important source of information in which more
and more customers base their purchasing decisions. They include
thousands of reviews concerning very different products and services
posted by many individuals geographically distributed all over the
world. Due to their massive audience, eWOM communities can help
users to find the product they are looking for even if they are less
popular or rare. This is known as the long tail effect, which leads to a
larger number of lower-selling niche products. This paper analyzes
the long tail effect in a well-known eWOM community and defines a
tool for finding niche products unavailable through conventional
channels.
Abstract: Despite the highly touted benefits, emerging
technologies have unleashed pervasive concerns regarding unintended
and unforeseen social impacts. Thus, those wishing to create safe and
socially acceptable products need to identify such side effects and
mitigate them prior to the market proliferation. Various methodologies
in the field of technology assessment (TA), namely Delphi, impact
assessment, and scenario planning, have been widely incorporated in
such a circumstance. However, literatures face a major limitation in
terms of sole reliance on participatory workshop activities. They
unfortunately missed out the availability of a massive untapped data
source of futuristic information flooding through the Internet. This
research thus seeks to gain insights into utilization of futuristic data,
future-oriented documents from the Internet, as a supplementary
method to generate social impact scenarios whilst capturing
perspectives of experts from a wide variety of disciplines. To this end,
network analysis is conducted based on the social keywords extracted
from the futuristic documents by text mining, which is then used as a
guide to produce a comprehensive set of detailed scenarios. Our
proposed approach facilitates harmonized depictions of possible
hazardous consequences of emerging technologies and thereby makes
decision makers more aware of, and responsive to, broad qualitative
uncertainties.
Abstract: The aim of this study was to build ‘Ubi-Net’, a
decision-making support system for systematic establishment in
U-City planning. We have experienced various urban problems caused
by high-density development and population concentrations in
established urban areas. To address these problems, a U-Service
contributes to the alleviation of urban problems by providing real-time
information to citizens through network connections and related
information. However, technology, devices, and information for
consumers are required for systematic U-Service planning in towns
and cities where there are many difficulties in this regard, and a lack of
reference systems.
Thus, this study suggests methods to support the establishment of
sustainable planning by providing comprehensive information
including IT technology, devices, news, and social networking
services (SNS) to U-City planners through intelligent searches. In this
study, we targeted Smart U-Parking Planning to solve parking
problems in an ‘old’ city. Through this study, we sought to contribute
to supporting advances in U-Space and the alleviation of urban
problems.
Abstract: Currently, there is excessively growing information
about places on Facebook, which is the largest social network but
such information is not explicitly organized and ranked. Therefore
users cannot exploit such data to recommend places conveniently and
quickly. This paper proposes a Facebook application and an Android
application that recommend places based on the number of check-ins
of those places, the distance of those places from the current location,
the number of people who like Facebook page of those places, and
the number of talking about of those places. Related Facebook data is
gathered via Facebook API requests. The experimental results of the
developed applications show that the applications can recommend
places and rank interesting places from the most to the least. We have
found that the average satisfied score of the proposed Facebook
application is 4.8 out of 5. The users’ satisfaction can increase by
adding the app features that support personalization in terms of
interests and preferences.
Abstract: The asynchronous discussion forum is one of the most
widely used activities in learning management system environment.
Online forum allows participants to interact, construct knowledge,
and can be used to complement face to face sessions in blended
learning courses. However, to what extent do the students perceive
the benefits or advantages of forum remain to be seen. Through
content and social network analyses, instructors will be able to gauge
the students’ engagement and knowledge construction level. Thus,
this study aims to analyze the students’ level of knowledge
construction and their participation level that occur through online
discussion. It also attempts to investigate the relationship between the
level of knowledge construction and their social interaction patterns.
The sample involves 23 students undertaking a master course in one
public university in Malaysia. The asynchronous discussion forum
was conducted for three weeks as part of the course requirement. The
finding indicates that the level of knowledge construction is quite
low. Also, the density value of 0.11 indicating the overall
communication among the participants in the forum is low. This
study reveals that strong and significant correlations between SNA
measures (in-degree centrality, out-degree centrality) and level of
knowledge construction. Thus, allocating these active students in
different group aids the interactive discussion takes place. Finally,
based upon the findings, some recommendations to increase students’
level of knowledge construction and also for further research are
proposed.
Abstract: This study aimed at investigating whether the
functional brain networks constructed using the initial EEG (obtained
when patients first visited hospital) can be correlated with the
progression of cognitive decline calculated as the changes of
mini-mental state examination (MMSE) scores between the latest and
initial examinations. We integrated the time–frequency cross mutual
information (TFCMI) method to estimate the EEG functional
connectivity between cortical regions, and the network analysis based
on graph theory to investigate the organization of functional networks
in aMCI. Our finding suggested that higher integrated functional
network with sufficient connection strengths, dense connection
between local regions, and high network efficiency in processing
information at the initial stage may result in a better prognosis of the
subsequent cognitive functions for aMCI. In conclusion, the functional
connectivity can be a useful biomarker to assist in prediction of
cognitive declines in aMCI.
Abstract: Brain functional networks based on resting-state EEG
data were compared between patients with mild Alzheimer’s disease
(mAD) and matched patients with amnestic subtype of mild cognitive
impairment (aMCI). We integrated the time–frequency cross mutual
information (TFCMI) method to estimate the EEG functional
connectivity between cortical regions and the network analysis based
on graph theory to further investigate the alterations of functional
networks in mAD compared with aMCI group. We aimed at
investigating the changes of network integrity, local clustering,
information processing efficiency, and fault tolerance in mAD brain
networks for different frequency bands based on several topological
properties, including degree, strength, clustering coefficient, shortest
path length, and efficiency. Results showed that the disruptions of
network integrity and reductions of network efficiency in mAD
characterized by lower degree, decreased clustering coefficient, higher
shortest path length, and reduced global and local efficiencies in the
delta, theta, beta2, and gamma bands were evident. The significant
changes in network organization can be used in assisting
discrimination of mAD from aMCI in clinical.
Abstract: The need to extract R&D keywords from issues and use
them to retrieve R&D information is increasing rapidly. However, it is
difficult to identify related issues or distinguish them. Although the
similarity between issues cannot be identified, with an R&D lexicon,
issues that always share the same R&D keywords can be determined.
In detail, the R&D keywords that are associated with a particular issue
imply the key technology elements that are needed to solve a particular
issue.
Furthermore, the relationship among issues that share the same
R&D keywords can be shown in a more systematic way by clustering
them according to keywords. Thus, sharing R&D results and reusing
R&D technology can be facilitated. Indirectly, redundant investment
in R&D can be reduced as the relevant R&D information can be shared
among corresponding issues and the reusability of related R&D can be
improved. Therefore, a methodology to cluster issues from the
perspective of common R&D keywords is proposed to satisfy these
demands.
Abstract: Non-Government Organizations (NGOs), Non-Profit Organizations (NPOs), Social Enterprises and other actors play an important role in political decisions in governments at the international levels. Especially, such organizations’ and activists’ network in civil society is quite important to effect to the global politics. To solve the complex social problems in global era, diverse actors should corporate each other. Moreover, network of protesters is also contributes to diffuse tactics, information and other resources of social movements.
Based on the findings from the study of International Trade Fairs (ITFs), the author analyzes the network of activists in anti-globalism movement. This research focuses the transition of 54 activists’ whole network in the “protest event” against 2008 G8 summit in Japan. Their network is examined at the three periods: Before protest event phase, during protest event phase and after event phase. A mixed method is used in this study: the author shows the hypothesis from social network analysis and evaluates that with interview data analysis.
This analysis gives the two results. Firstly, the more protesters participate to the various events during the protest event, the more they build the network. After that, active protesters keep their network as well. From interview data, we can understand that the active protesters can build their network and diffuse the information because they communicate with other participants and understand that diverse issues are related.
This paper comes to same conclusion with previous researches: protest events activate the network among the political activists. However, some participants succeed to build their network, others do not. “Networked” activists are participated in the various events for short period of time and encourage the diffusion of information and tactics of social movements.
Abstract: One of the most significant threats to the economy of a nation is the bankruptcy of its banks. This study evaluates the susceptibility of Nigerian banks to failure with a view to identifying ratios and financial data that are sensitive to solvency of the bank. Further, a predictive model is generated to guide all stakeholders in the industry. Thirty quoted banks that had published Annual Reports for the year preceding the consolidation i.e. year 2004 were selected. They were examined for distress using the Multilayer Perceptron Neural Network Analysis. The model was used to analyze further reforms by the Central Bank of Nigeria using published Annual Reports of twenty quoted banks for the year 2008 and 2011. The model can thus be used for future prediction of failure in the Nigerian banking system.
Abstract: Gene networks present a graphical view at the level of gene activities and genetic functions and help us to understand complex interactions in a meaningful manner. In the present study, we have analyzed the gene interaction of PPAR-γ (peroxisome proliferator-activated receptor gamma) by search tool for retrieval of interacting genes. We find PPAR-γ is highly networked by genetic interactions with 10 genes: RXRA (retinoid X receptor, alpha), PPARGC1A (peroxisome proliferator-activated receptor gamma, coactivator 1 alpha), NCOA1 (nuclear receptor coactivator 1), NR0B2 (nuclear receptor subfamily 0, group B, member 2), HDAC3 (histone deacetylase 3), MED1 (mediator complex subunit 1), INS (insulin), NCOR2 (nuclear receptor co-repressor 2), PAX8 (paired box 8), ADIPOQ (adiponectin) and it augurs well for the fact that obesity and several other metabolic disorders are inter related.
Abstract: The objective of this work is to explicit knowledge on the interactions between the chlorophyll-a and nine meroplankton larvae of epibenthonic fauna. The studied case is the Arraial do Cabo upwelling system, Southeastern of Brazil, which provides different environmental conditions. To assess this information a network approach based in probability estimative was used. Comparisons among the generated graphs are made in the light of different water masses, application of Shannon biodiversity index, and the closeness and betweenness centralities measurements. Our results show the main pattern among different water masses and how the core organisms belonging to the network skeleton are correlated to the main environmental variable. We conclude that the approach of complex networks is a promising tool for environmental diagnostic.
Abstract: In social network analysis the mean nodal degree and
density of the graph can be considered as a measure of the activity of
all actors in the network and this is an important property of a graph
and for making comparisons among networks. Since subjects in a
family or organization are subject to common environment factors, it
is prime interest to study the association between responses.
Therefore, we study the distribution of the mean nodal degree and
density of the graph under correlated binary units. The cross product
ratio is used to capture the intra-units association among subjects.
Computer program and an application are given to show the benefits
of the method.
Abstract: As increasing importance of symbiosis and cooperation among mobile communication industries, the mobile ecosystem has been especially highlighted in academia and practice. The structure of mobile ecosystem is quite complex and the ecological role of actors is important to understand that structure. In this respect, this study aims to explore structure of mobile ecosystem in the case of Korea using inter-industry network analysis. Then, the ecological roles in mobile ecosystem are identified using centrality measures as a result of network analysis: degree of centrality, closeness, and betweenness. The result shows that the manufacturing and service industries are separate. Also, the ecological roles of some actors are identified based on the characteristics of ecological terms: keystone, niche, and dominator. Based on the result of this paper, we expect that the policy makers can formulate the future of mobile industry and healthier mobile ecosystem can be constructed.
Abstract: since in natural accidents, facilities that relate to this vita element are underground so, it is difficult to find quickly some right, exact and definite information about water utilities. There fore, this article has done operationally in Boukan city in Western Azarbaijan of Iran and it tries to represent operation and capabilities of Geographical Information system (GIS) in urban water management at the time of natural accidents. Structure of this article is that firstly it has established a comprehensive data base related to water utilities by collecting, entering, saving and data management, then by modeling water utilities we have practically considered its operational aspects related to water utility problems in urban regions.
Abstract: Existing proceeding-models for the development of mechatronic systems provide a largely parallel action in the detailed development. This parallel approach is to take place also largely independent of one another in the various disciplines involved. An approach for a new proceeding-model provides a further development of existing models to use for the development of Adaptronic Systems. This approach is based on an intermediate integration and an abstract modeling of the adaptronic system. Based on this system-model a simulation of the global system behavior, due to external and internal factors or Forces is developed. For the intermediate integration a special data management system is used. According to the presented approach this data management system has a number of functions that are not part of the "normal" PDM functionality. Therefore a concept for a new data management system for the development of Adaptive system is presented in this paper. This concept divides the functions into six layers. In the first layer a system model is created, which divides the adaptronic system based on its components and the various technical disciplines. Moreover, the parameters and properties of the system are modeled and linked together with the requirements and the system model. The modeled parameters and properties result in a network which is analyzed in the second layer. From this analysis necessary adjustments to individual components for specific manipulation of the system behavior can be determined. The third layer contains an automatic abstract simulation of the system behavior. This simulation is a precursor for network analysis and serves as a filter. By the network analysis and simulation changes to system components are examined and necessary adjustments to other components are calculated. The other layers of the concept treat the automatic calculation of system reliability, the "normal" PDM-functionality and the integration of discipline-specific data into the system model. A prototypical implementation of an appropriate data management with the addition of an automatic system development is being implemented using the data management system ENOVIA SmarTeam V5 and the simulation system MATLAB.
Abstract: One of research issues in social network analysis is to
evaluate the position/importance of users in social networks. As the
information diffusion in social network is evolving, it seems difficult
to evaluate the importance of users using traditional approaches. In
this paper, we propose an evaluation approach for user importance
with fractal view in social networks. In this approach, the global importance
(Fractal Importance) and the local importance (Topological
Importance) of nodes are considered. The basic idea is that the bigger
the product of fractal importance and topological importance of a
node is, the more important of the node is. We devise the algorithm
called TFRank corresponding to the proposed approach. Finally, we
evaluate TFRank by experiments. Experimental results demonstrate
our TFRank has the high correlations with PageRank algorithm
and potential ranking algorithm, and it shows the effectiveness and
advantages of our approach.
Abstract: The population structure of the Tor tambroides was
investigated with morphometric data (i.e. morphormetric
measurement and truss measurement). A morphometric analysis was
conducted to compare specimens from three waterfalls: Sunanta, Nan
Chong Fa and Wang Muang waterfalls at Khao Nan National Park,
Nakhon Si Thammarat, Southern Thailand. The results of stepwise
discriminant analysis on seven morphometric variables and 21 truss
variables per individual were the same as from a neural network. Fish
from three waterfalls were separated into three groups based on their
morphometric measurements. The morphometric data shows that the
nerual network model performed better than the stepwise
discriminant analysis.