  In June 2013, Brazil faced the largest and most significant mass protests in
a generation. These were exacerbated by the population's disenchantment towards
its highly fragmented party system, which is composed by a very large number of
political parties. Under these circumstances, presidents are constrained by
informal coalition governments, bringing very harmful consequences to the
country. In this work I propose ARRANGE, a dAta dRiven method foR Assessing and
reduciNG party fragmEntation in a country. ARRANGE uses as input the roll call
data for congress votes on bills and amendments as a proxy for political
preferences and ideology. With that, ARRANGE finds the minimum number of
parties required to house all congressmen without decreasing party discipline.
When applied to Brazil's historical roll call data, ARRANGE was able to
generate 23 distinct configurations that, compared with the status quo, have
(i) a significant smaller number of parties, (ii) a higher discipline of
partisans towards their parties and (iii) a more even distribution of partisans
into parties. ARRANGE is fast and parsimonious, relying on a single, intuitive
parameter.
