  In this paper we present a social network and forensic analysis of the vote
counts of Spanish national elections that took place in December 2015 and their
sequel in June 2016. Vote counts are extracted at the level of municipalities,
yielding an unusually high resolution dataset with over 8000 samples. We
initially consider the phenomenon of Bipartisanship breakdown by analysing
spatial distributions of several Bipartisanship indices. We find that such
breakdown is more prominent close to cosmopolite and largely populated areas
and less important in rural areas where Bipartisanship still prevails, and its
evolution mildly consolidates in the 2016 round, with some evidence of
Bipartisanship reinforcement which we hypothesize to be due to psychological
mechanisms of risk aversion. On a third step we explore to which extent vote
data are faithful by applying forensic techniques to vote statistics. We first
explore the conformance of first digit distributions to Benford's law for each
of the main political parties. The results and interpretations are mixed and
vary across different levels of aggregation, finding a general good
quantitative agreement at the national scale for both municipalities and
precincts but finding systematic nonconformance at the level of individual
precincts. As a complementary metric, we further explore the co-occurring
statistics of voteshare and turnout, finding a mild tendency in the clusters of
the conservative party to smear out towards the area of high turnout and
voteshare, what has been previously interpreted as a possible sign of
incremental fraud. In every case results are qualitatively similar between 2015
and 2016 elections.
