Community detection, also known as graph clustering, in multi-layer networks has been extensively studied in the literature. The goal of community detection is to partition vertices in a network into densely connected components so called communities. Networks contain a set of strong, dominant communities, which may interfere with the detection of weak, natural community structure. When most of the members of the weak communities also belong to stronger communities, they are extremely hard to be uncovered. We call the weak communities the hidden or disguised community structure. In this paper, we present a method to uncover weak communities in a network by weakening the strength of the dominant structure. With the aim to detect the weak communities, through experiments, we observe real-world networks to answer the question of whether real-world networks have hidden community structure or not. Results of the hidden community detection (HCD) method showed the great variation in the number of communities detected in multiple layers when compared with the results of other community detection methods.
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