264,281 research outputs found
The dynamics of global R&D collaboration networks in ICT: Does China catch up with the US?
The purpose of this study is to identify and characterize the structure and Dynamics of global R&D collaboration Networks in ICT by analyzing cross-country co-patents, with a special focus on the role of China. We employ a Social Network Analysis(SNA)perspective, using information on more than 77 thousand co-patents from 2001–2015. The seco-patents are disaggregated by three time periods and four ICT subsectors. Global measures for the net-work as a whole, as well as local measures on the positioning of countries in the networks are interpreted. The empirical results are highly interesting. First, international R&D collaboration networks in ICT show a dynamic transformation in becoming larger in magnitude (more countries but also more inter-linkages), less centralized and more densely connected, though with varying degrees across ICT subsectors. Second, the powerful position of the US weakens relatively compared to other, increasingly connected countries, in particular China. While China has already surpassed the US in total patenting in ICT in 2015, China is now also catching up from a Network perspective shown by its growing central position over the observed time period
NodeTrix: Hybrid Representation for Analyzing Social Networks
The need to visualize large social networks is growing as hardware
capabilities make analyzing large networks feasible and many new data sets
become available. Unfortunately, the visualizations in existing systems do not
satisfactorily answer the basic dilemma of being readable both for the global
structure of the network and also for detailed analysis of local communities.
To address this problem, we present NodeTrix, a hybrid representation for
networks that combines the advantages of two traditional representations:
node-link diagrams are used to show the global structure of a network, while
arbitrary portions of the network can be shown as adjacency matrices to better
support the analysis of communities. A key contribution is a set of interaction
techniques. These allow analysts to create a NodeTrix visualization by dragging
selections from either a node-link or a matrix, flexibly manipulate the
NodeTrix representation to explore the dataset, and create meaningful summary
visualizations of their findings. Finally, we present a case study applying
NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate
the capabilities of NodeTrix as both an exploration tool and an effective means
of communicating results
The Lifecycle and Cascade of WeChat Social Messaging Groups
Social instant messaging services are emerging as a transformative form with
which people connect, communicate with friends in their daily life - they
catalyze the formation of social groups, and they bring people stronger sense
of community and connection. However, research community still knows little
about the formation and evolution of groups in the context of social messaging
- their lifecycles, the change in their underlying structures over time, and
the diffusion processes by which they develop new members. In this paper, we
analyze the daily usage logs from WeChat group messaging platform - the largest
standalone messaging communication service in China - with the goal of
understanding the processes by which social messaging groups come together,
grow new members, and evolve over time. Specifically, we discover a strong
dichotomy among groups in terms of their lifecycle, and develop a separability
model by taking into account a broad range of group-level features, showing
that long-term and short-term groups are inherently distinct. We also found
that the lifecycle of messaging groups is largely dependent on their social
roles and functions in users' daily social experiences and specific purposes.
Given the strong separability between the long-term and short-term groups, we
further address the problem concerning the early prediction of successful
communities. In addition to modeling the growth and evolution from group-level
perspective, we investigate the individual-level attributes of group members
and study the diffusion process by which groups gain new members. By
considering members' historical engagement behavior as well as the local social
network structure that they embedded in, we develop a membership cascade model
and demonstrate the effectiveness by achieving AUC of 95.31% in predicting
inviter, and an AUC of 98.66% in predicting invitee.Comment: 10 pages, 8 figures, to appear in proceedings of the 25th
International World Wide Web Conference (WWW 2016
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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