%0 Conference Paper %B 7th Workshop on Complex Networks %D 2016 %T A novel approach to evaluate community detection algorithms on ground truth %A Giulio Rossetti %A Luca Pappalardo %A S Rinzivillo %X Evaluating 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. %B 7th Workshop on Complex Networks %I Springer-Verlag %C Dijon, France %G eng %U http://www.giuliorossetti.net/about/wp-content/uploads/2015/12/Complenet16.pdf %R 10.1007/978-3-319-30569-1_10