A novel approach to evaluate community detection algorithms on ground truth

You are here

TitleA novel approach to evaluate community detection algorithms on ground truth
Publication TypeConference Paper
Year of Publication2016
AuthorsRossetti, G, Pappalardo, L, Rinzivillo, S
Conference Name7th Workshop on Complex Networks
PublisherSpringer-Verlag
Conference LocationDijon, France
AbstractEvaluating a community detection algorithm is a complex task due to the lack of a shared and universally accepted definition of community. In literature, one of the most common way to assess the performances of a community detection algorithm is to compare its output with given ground truth communities by using computationally expensive metrics (i.e., Normalized Mutual Information). In this paper we propose a novel approach aimed at evaluating the adherence of a community partition to the ground truth: our methodology provides more information than the state-of-the-art ones and is fast to compute on large-scale networks. We evaluate its correctness by applying it to six popular community detection algorithms on four large-scale network datasets. Experimental results show how our approach allows to easily evaluate the obtained communities on the ground truth and to characterize the quality of community detection algorithms.
URLhttp://www.giuliorossetti.net/about/wp-content/uploads/2015/12/Complenet16.pdf
DOI10.1007/978-3-319-30569-1_10
Research Project: