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Local community finding algorithms are helpful for finding communities around a seed node especially when the network is large and a global method is too slow. Most local methods find only a single community or are required to be run several times over ...

Community finding algorithms strive to find communities that have a higher connectivity within the communities than between them. Recently a framework called the community set space was introduced which provided a way to measure the quality of community ...

In this paper, we propose a density-based community detection method, CMiner, which exploits the interaction graph of online social networks to identify overlapping community structures. Based on the average reciprocated interactions of a node in the ...

Finding communities in networks is a hot topic in several research areas like social network, graph theory or sociology among others. This work considers the community finding problem as a clustering problem where an evolutionary approach can provide a ...

This paper presents the community set space canvas, a triangular canvas where the results of community finding algorithms can be plotted for comparison. The points of the triangle represent trivial sets, such as the set of one large community, and the ...

In this paper, we analyze and compare the performance of four different community detection algorithms, each following a different approach. The performance of the algorithms is compared on a variety of benchmark graphs with known community structure. ...

Real-world social networks from a variety of domains can naturally be modelled as dynamic graphs. However, approaches to detecting communities have largely focused on identifying communities in static graphs. Recently, researchers have begun to consider ...

Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised learning algorithm that uses Gaussian fields and harmonic functions. This ...

Expanding a seed set into a larger community is a common procedure in link-based analysis. We show how to adapt recent results from theoretical computer science to expand a seed set into a community with small conductance and a strong relationship to ...