Community detection in node-attributed social networks: a survey
P Chunaev - Computer Science Review, 2020 - Elsevier
Community detection is a fundamental problem in social network analysis consisting,
roughly speaking, in unsupervised dividing social actors (modeled as nodes in a social …
roughly speaking, in unsupervised dividing social actors (modeled as nodes in a social …
Community detection in multiplex networks
A multiplex network models different modes of interaction among same-type entities. In this
article, we provide a taxonomy of community detection algorithms in multiplex networks. We …
article, we provide a taxonomy of community detection algorithms in multiplex networks. We …
A survey of community detection methods in multilayer networks
X Huang, D Chen, T Ren, D Wang - Data Mining and Knowledge …, 2021 - Springer
Community detection is one of the most popular researches in a variety of complex systems,
ranging from biology to sociology. In recent years, there's an increasing focus on the rapid …
ranging from biology to sociology. In recent years, there's an increasing focus on the rapid …
A survey about community detection over On-line Social and Heterogeneous Information Networks
Abstract In modern Online Social Networks (OSNs), the need to detect users' communities
based on their interests and social connections has became a more and more important …
based on their interests and social connections has became a more and more important …
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
Sensibly highlighting the hidden structures of many real-world networks has attracted
growing interest and triggered a vast array of techniques on what is called nowadays …
growing interest and triggered a vast array of techniques on what is called nowadays …
Characterizing communities of hashtag usage on twitter during the 2020 COVID-19 pandemic by multi-view clustering
The COVID-19 pandemic has produced a flurry of online activity on social media sites. As
such, analysis of social media data during the COVID-19 pandemic can produce unique …
such, analysis of social media data during the COVID-19 pandemic can produce unique …
Multilayer network simplification: approaches, models and methods
Multilayer networks have been widely used to represent and analyze systems of
interconnected entities where both the entities and their connections can be of different …
interconnected entities where both the entities and their connections can be of different …
The atlas for the aspiring network scientist
M Coscia - arxiv preprint arxiv:2101.00863, 2021 - arxiv.org
Network science is the field dedicated to the investigation and analysis of complex systems
via their representations as networks. We normally model such networks as graphs: sets of …
via their representations as networks. We normally model such networks as graphs: sets of …
Topological clustering of multilayer networks
Multilayer networks continue to gain significant attention in many areas of study, particularly
due to their high utility in modeling interdependent systems such as critical infrastructures …
due to their high utility in modeling interdependent systems such as critical infrastructures …
Discriminative adversarial domain generalization with meta-learning based cross-domain validation
The generalization capability of machine learning models, which refers to generalizing the
knowledge for an “unseen” domain via learning from one or multiple seen domain (s), is of …
knowledge for an “unseen” domain via learning from one or multiple seen domain (s), is of …