  We investigate the properties of correlation based networks originating from
economic complex systems, such as the network of stocks traded at the New York
Stock Exchange (NYSE). The weaker links (low correlation) of the system are
found to contribute to the overall connectivity of the network significantly
more than the strong links (high correlation). We find that nodes connected
through strong links form well defined communities. These communities are
clustered together in more complex ways compared to the widely used
classification according to the economic activity. We find that some companies,
such as General Electric (GE), Coca Cola (KO), and others, can be involved in
different communities. The communities are found to be quite stable over time.
Similar results were obtained by investigating markets completely different in
size and properties, such as the Athens Stock Exchange (ASE). The present
method may be also useful for other networks generated through correlations.
