  In this paper, we introduce a network-based methodology to study how clusters
represented by political entities evolve over time. We constructed networks of
voting data from the Brazilian Chamber of Deputies, where deputies are nodes
and edges are represented by voting similarity among deputies. The Brazilian
Chamber of deputies is characterized by a multi-party political system. Thus,
we would expect a broad spectrum of ideas to be represented. Our results,
however, revealed that plurality of ideas is not present at all: the effective
number of communities representing ideas based on agreement/disagreement in
propositions is about 3 over the entire studied time span. The obtained results
also revealed different patterns of coalitions between distinct parties.
Finally, we also found signs of early party isolation before presidential
impeachment proceedings effectively started. We believe that the proposed
framework could be used to complement the study of political dynamics and even
applied in similar social networks where individuals are organized in a complex
manner.
