相关论文: Quantitative Analysis of Community Evolution in De…
Community detection, a fundamental task for network analysis, aims to partition a network into multiple sub-structures to help reveal their latent functions. Community detection has been extensively studied in and broadly applied to many…
Background: Open Source Software (OSS) started as an effort of communities of volunteers, but its practices have been adopted far beyond these initial scenarios. For instance, the strategic use of OSS in industry is constantly growing…
Community detection is a crucial task to unravel the intricate dynamics of online social networks. The emergence of these networks has dramatically increased the volume and speed of interactions among users, presenting researchers with…
Governments are increasingly employing funding for open source software (OSS) development as a policy lever to support the security of software supply chains, digital sovereignty, economic growth, and national competitiveness in science and…
1. Joint Species Distribution models (JSDMs) explain spatial variation in community composition by contributions of the environment, biotic associations, and possibly spatially structured residual covariance. They show great promise as a…
Many software projects are no longer done in-house by a single organization. Instead, we are in a new age where software is developed by a networked community of individuals and organizations, which base their relations to each other on…
Ecologists are interested in understanding and predicting how ecological communities change through time. While it might seem natural to measure this through changes in species' abundances, computational limitations mean transitions between…
Communities in social networks often reflect close social ties between their members and their evolution through time. We propose an approach that tracks two aspects of community evolution in retweet networks: flow of the members in, out…
Today's dynamic and iterative development environment brings significant challenges for software project management. In distributed project settings, "management by walking around" is no longer an option and project managers may miss out on…
We introduce an intuitive model that describes both the emergence of community structure and the evolution of the internal structure of communities in growing social networks. The model comprises two complementary mechanisms: One mechanism…
Community detection is an important tool for analyzing the social graph of mobile phone users. The problem of finding communities in static graphs has been widely studied. However, since mobile social networks evolve over time, static graph…
Discovering communities in complex networks helps to understand the behaviour of the network. Some works in this promising research area exist, but communities uncovering in time-dependent and/or multiplex networks has not deeply…
Online creative communities have been able to develop large, open source software (OSS) projects like Linux and Firefox throughout the successful collaborations carried out over the Internet. These communities have also expanded to creative…
We propose an automated and unsupervised methodology for a novel summarization of group behavior based on content preference. We show that graph theoretical community evolution (based on similarity of user preference for content) is…
Discovering and tracking communities in time-varying networks is an important task in network science, motivated by applications in fields ranging from neuroscience to sociology. In this work, we characterize the celebrated family of…
[Context] Open Source Software (OSS) is nowadays used and integrated in most of the commercial products. However, the selection of OSS projects for integration is not a simple process, mainly due to a of lack of clear selection models and…
Community detection can be considered as a variant of cluster analysis applied to complex networks. For this reason, all existing studies have been using tools derived from this field when evaluating community detection algorithms. However,…
Many methods have been proposed to detect communities, not only in plain, but also in attributed, directed or even dynamic complex networks. From the modeling point of view, to be of some utility, the community structure must be…
Scientific open-source software (OSS) has greatly benefited research communities through its transparent and collaborative nature. Given its critical role in scientific research, ensuring the sustainability of such software has become…
Community detection, or clustering, identifies groups of nodes in a graph that are more densely connected to each other than to the rest of the network. Given the size and dynamic nature of real-world graphs, efficient community detection…