<p>There are a lot. The term is "<em>Overlapping community detection</em>".</p>

<p>Take a look at this paper, for example, where you can find comparison of 14 such algorithms:</p>

<p><a href="http://arxiv.org/abs/1110.5813" rel="nofollow">Overlapping Community Detection in Networks: the State of the Art and Comparative Study [Xie, Kelley, Szymanski - 2011]</a></p>

<p><a href="https://cs.stanford.edu/people/jure/pubs/bigclam-wsdm13.pdf" rel="nofollow">BIGCLAM</a>, an algorithm presented by Yang and Leskovec is an interesting one, as it scales very well. It is available as part of <a href="https://snap.stanford.edu/snap/description.html" rel="nofollow">SNAP</a>.</p>
Community detection: Any algorithm that assigns a person to multiple communities?
<p>I feel in some cases it is reasonable for a person to be assigned to multiple communities. For example in the science field a professor may work in multiple research areas. Is there an algorithm that assigns a person to multiple communities, or a "soft-labeling approach"?(e.g. a positive probability associated with a person belonging to any detected community)</p>

<p>Thanks</p>