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ERIS: An Approach Based on Community Boundaries to Assess Polarization in Online Social Networks
Detection and characterization of polarization are of major interest in Social Network Analysis, especially to identify conflictual topics that...
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A Unified Stream and Batch Graph Computing Model for Community Detection
An essential challenge in graph data analysis and mining is to simply and effectively deal with large-scale network data that is expanding...
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Percolation and Epidemic Processes in One-Dimensional Small-World Networks
We obtain tight thresholds for bond percolation on one-dimensional small-world graphs, and apply such results to obtain tight thresholds for the...
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Community and topic modeling for infectious disease clinical trial recommendation
Clinical trials are crucial for the advancement of treatment and knowledge within the medical community. Although the ClinicalTrials.gov initiative...
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Wilson’s disease classification using higher-order Gabor tensors and various classifiers on a small and imbalanced brain MRI dataset
Wilson’s Disease (WD) is a rare, autosomal recessive disorder caused by excessive accumulation of Copper (Cu) in various human organs such as the...
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How Potential New Members Approach an Online Community
Online communities, socio-technical systems where people interact with others, depend on new members coming to the community. While the majority of...
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Experiences of face-to-face and online collaborative learning tutorials: A qualitative community of inquiry approach
This study explores the experiences and the preferred schedule of face-to-face and online tutorials in a problem-based learning setting where...
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An empirical characterization of community structures in complex networks using a bivariate map of quality metrics
Community detection emerges as an important task in the discovery of network mesoscopic structures. However, the concept of a “good” community is...
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Biometric Iris Identifier Recognition with Privacy Preserving Phenomenon: A Federated Learning Approach
As technology is getting advanced day by day, the concern of security, authentication, and identification are also becoming important in every...
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CDGCN: An Effective and Efficient Algorithm Based on Community Detection for Training Deep and Large Graph Convolutional Networks
Graph convolution neural network (GCN) has become a critical tool to capture representations of graph nodes. At present, the graph convolution model...
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Community Detection Based on Deep Network Embedding with Dual Self-supervised Training
We propose a community discovery method based on deep auto-encoding (DGAE_DST). Firstly, we use the pre-trained two-layer neural network and k-means...
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Extending the “Smart City” Concept to Small-to-Medium Sized Estonian Municipalities: Initiatives and Challenges Faced
This study investigated smart city initiatives and challenges faced by small to medium sized municipalities. The literature on smart cities is...
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A Local Seeding Algorithm for Community Detection in Dynamic Networks
Discovering communities by seed expansion is a good alternative in large networks as well as dynamic networks, since it only requires exploring the...
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Community detection in social recommender systems: a survey
Information extracted from social network services promise to improve the accuracy of recommender systems in various domains. Against this...
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Where do migrants and natives belong in a community: a Twitter case study and privacy risk analysis
Today, many users are actively using Twitter to express their opinions and to share information. Thanks to the availability of the data, researchers...
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A spiderweb model for community detection in dynamic networks
Community detection in dynamic networks is one of the most challenging tasks in the field of network analysis. In general, networks often evolve...
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The Ugly Side of Stack Overflow: An In-depth Exploration of the Social Dynamics of New Users’ Engagement and Community Perception of Them
Stack Overflow (SO) is the most popular knowledge-sharing platform for novice to experienced programmers. It is growing gradually with its rapidly...
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I/O efficient k-truss community search in massive graphs
Community detection that discovers all densely connected communities in a network has been studied a lot. In this paper, we study online community search...
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Multiple Local Community Detection via High-Quality Seed Identification over Both Static and Dynamic Networks
Local community detection aims to find the communities that a given seed node belongs to. Most existing works on this problem are based on a very...
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Learning network embeddings using small graphlets
Techniques for learning vectorial representations of graphs ( graph embeddings ) have recently emerged as an effective approach to facilitate machine...
