Exploring the Importance of Negative Links through the European Parliament Social Graph

In this paper, we study the informative value of negative links in social networks, more specifically signed networks. We first process a selection of networks, generated from the 7th term (2009-2014), that were constructed by considering voting similarities between Members of the European Parliament. We propose a rework of Parallel Iterative Local Search; An algorithm to partition networks by means of solving the Correlation Clustering Problem, which takes in consideration the sign of the edges when generating selecting the communities for each node. Our rework reduces the termination time of the algorithm, and performs a faster exploration of the solution space, by means of limiting the number of iterations in local searches and also imposes a condition for a perturbation to be processed. Our approach reduced the termination required time to around 10% of the original approach, besides being able to reach better results when compared with a selection of community detection algorithms like Infomap and Walktrap, designed to process only positive links.