A fundamental technical challenge in the analysis of network data is the automated discovery of communities - groups of nodes that are strongly connected or that share similar features or roles. In this commentary we review progress in the field over the last 20 years.Comment: 6 pages, 1 figure. Published in Nature Physic
Networks have become a common data mining tool to encode relational definitions between a set of ent...
In this thesis, we first explore two different approaches to efficient community detection that addr...
Empirical analysis of network data has been widely conducted for understanding and predicting the st...
A fundamental technical challenge in the analysis of network data is the automated discovery of comm...
Background Community structure is one of the key properties of complex networks and plays a crucial ...
BACKGROUND: Community structure is one of the key properties of complex networks and plays a crucial...
The existence of community structures in networks is not unusual, including in the domains of sociol...
The problem of community detection is relevant in many disciplines of science. A community is usuall...
Recently, it was recognized that the problems lying between the order and chaos require a new scient...
Real world complex networks may contain hidden structures called communities or groups. They are com...
There has been considerable recent interest in algorithms for finding communities in networks—groups...
Recent advances in computing and measurement technologies have led to an explosion in the amount of ...
The characterization of network community structure has profound implications in several scientific ...
This is the final version. Available from the publisher via the DOI in this record.Network science p...
Community detection is an important aspect of network analysis that has far-reaching consequences, i...
Networks have become a common data mining tool to encode relational definitions between a set of ent...
In this thesis, we first explore two different approaches to efficient community detection that addr...
Empirical analysis of network data has been widely conducted for understanding and predicting the st...
A fundamental technical challenge in the analysis of network data is the automated discovery of comm...
Background Community structure is one of the key properties of complex networks and plays a crucial ...
BACKGROUND: Community structure is one of the key properties of complex networks and plays a crucial...
The existence of community structures in networks is not unusual, including in the domains of sociol...
The problem of community detection is relevant in many disciplines of science. A community is usuall...
Recently, it was recognized that the problems lying between the order and chaos require a new scient...
Real world complex networks may contain hidden structures called communities or groups. They are com...
There has been considerable recent interest in algorithms for finding communities in networks—groups...
Recent advances in computing and measurement technologies have led to an explosion in the amount of ...
The characterization of network community structure has profound implications in several scientific ...
This is the final version. Available from the publisher via the DOI in this record.Network science p...
Community detection is an important aspect of network analysis that has far-reaching consequences, i...
Networks have become a common data mining tool to encode relational definitions between a set of ent...
In this thesis, we first explore two different approaches to efficient community detection that addr...
Empirical analysis of network data has been widely conducted for understanding and predicting the st...
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