51,609 research outputs found
Communities, Knowledge Creation, and Information Diffusion
In this paper, we examine how patterns of scientific collaboration contribute
to knowledge creation. Recent studies have shown that scientists can benefit
from their position within collaborative networks by being able to receive more
information of better quality in a timely fashion, and by presiding over
communication between collaborators. Here we focus on the tendency of
scientists to cluster into tightly-knit communities, and discuss the
implications of this tendency for scientific performance. We begin by reviewing
a new method for finding communities, and we then assess its benefits in terms
of computation time and accuracy. While communities often serve as a taxonomic
scheme to map knowledge domains, they also affect how successfully scientists
engage in the creation of new knowledge. By drawing on the longstanding debate
on the relative benefits of social cohesion and brokerage, we discuss the
conditions that facilitate collaborations among scientists within or across
communities. We show that successful scientific production occurs within
communities when scientists have cohesive collaborations with others from the
same knowledge domain, and across communities when scientists intermediate
among otherwise disconnected collaborators from different knowledge domains. We
also discuss the implications of communities for information diffusion, and
show how traditional epidemiological approaches need to be refined to take
knowledge heterogeneity into account and preserve the system's ability to
promote creative processes of novel recombinations of idea
Community structures and role detection in music networks
We analyze the existence of community structures in two different social
networks obtained from similarity and collaborative features between musical
artists. Our analysis reveals some characteristic organizational patterns and
provides information about the driving forces behind the growth of the
networks. In the similarity network, we find a strong correlation between
clusters of artists and musical genres. On the other hand, the collaboration
network shows two different kinds of communities: rather small structures
related to music bands and geographic zones, and much bigger communities built
upon collaborative clusters with a high number of participants related through
the period the artists were active. Finally, we detect the leading artists
inside their corresponding communities and analyze their roles in the network
by looking at a few topological properties of the nodes.Comment: 14 pages 7 figure
Tag-Aware Recommender Systems: A State-of-the-art Survey
In the past decade, Social Tagging Systems have attracted increasing
attention from both physical and computer science communities. Besides the
underlying structure and dynamics of tagging systems, many efforts have been
addressed to unify tagging information to reveal user behaviors and
preferences, extract the latent semantic relations among items, make
recommendations, and so on. Specifically, this article summarizes recent
progress about tag-aware recommender systems, emphasizing on the contributions
from three mainstream perspectives and approaches: network-based methods,
tensor-based methods, and the topic-based methods. Finally, we outline some
other tag-related works and future challenges of tag-aware recommendation
algorithms.Comment: 19 pages, 3 figure
On time-varying collaboration networks
The patterns of scientific collaboration have been frequently investigated in
terms of complex networks without reference to time evolution. In the present
work, we derive collaborative networks (from the arXiv repository)
parameterized along time. By defining the concept of affine group, we identify
several interesting trends in scientific collaboration, including the fact that
the average size of the affine groups grows exponentially, while the number of
authors increases as a power law. We were therefore able to identify, through
extrapolation, the possible date when a single affine group is expected to
emerge. Characteristic collaboration patterns were identified for each
researcher, and their analysis revealed that larger affine groups tend to be
less stable
Scientometric mapping as a strategic intelligence tool for the governance of emerging technologies
How can scientometric mapping function as a tool of ’strategic intelligence’ to aid the governance of emerging technologies? The present paper aims to address this question by focusing on a set of recently developed scientometric techniques, namely overlay mapping. We examine the potential these techniques have to inform, in a timely manner, analysts and decision-makers about relevant dynamics of technical emergence. We investigate the capability of overlay mapping in generating informed perspectives about emergence across three spaces: geographical, social, and cognitive. Our analysis relies on three empirical studies of emerging technologies in the biomedical domain: RNA interference (RNAi), Human Papilloma Virus (HPV) testing technologies for cervical cancer, and Thiopurine Methyltransferase (TPMT) genetic testing. The case-studies are analysed and mapped longitudinally by using publication and patent data. Results show the variety of ’intelligence’ inputs overlay mapping can produce for the governance of emerging technologies. Overlay mapping also confers to the investigation of emergence flexibility and granularity in terms of adaptability to different sources of data and selection of the levels of the analysis, respectively. These features make possible the integration and comparison of results from different contexts and cases, thus providing possibilities for a potentially more ’distributed’ strategic intelligence.
The generated perspectives allow triangulation of findings, which is important given the complexity featuring in technical emergence and the limitations associated with the use of single scientometric approaches
Supporting social innovation through visualisations of community interactions
Online communities that form through the introduction of sociotechnical platforms require significant effort to cultivate and sustain. Providing open, transparent information on community behaviour can motivate participation from community members themselves, while also providing platform administrators with detailed interaction dynamics. However, challenges arise in both understanding what information is conducive to engagement and sustainability, and then how best to represent this information to platform stakeholders. Towards a better understanding of these challenges, we present the design, implementation, and evaluation of a set of simple visualisations integrated into a Collective Awareness Platform for Social Innovation platform titled commonfare.net. We discuss the promise and challenge of bringing social innovation into the digital age, in terms of supporting sustained platform use and collective action, and how the introduction of community visualisations has been directed towards achieving this goal
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