  Political polarization in online social platforms is a rapidly growing
phenomenon worldwide. Despite their relevance to modern-day politics, the
structure and dynamics of polarized states in digital spaces are still poorly
understood. We analyze the community structure of a two-layer, interconnected
network of French Twitter users, where one layer contains members of Parliament
and the other one regular users. We obtain an optimal representation of the
network in a four-dimensional political opinion space by combining network
embedding methods and political survey data. We find structurally cohesive
groups sharing common political attitudes and relate them to the political
party landscape in France. The distribution of opinions of professional
politicians is narrower than that of regular users, indicating the presence of
more extreme attitudes in the general population. We find that politically
extreme communities interact less with other groups as compared to more
centrist groups. We apply an empirically tested social influence model to the
two-layer network to pinpoint interaction mechanisms that can describe the
political polarization seen in data, particularly for centrist groups. Our
results shed light on the social behaviors that drive digital platforms towards
polarization, and uncover an informative multidimensional space to assess
political attitudes online.
