In this paper we introduce an innovative method to diagnose electoral fraud using vote counts. First, to circumvent data availability problems and to study a particular type of fraud, we create synthetic data using Monte Carlo methods. Next, we build a supervised machine learning tool and use a...

Authoritarian elections have been linked to both regime longevity and implicated in regime change, raising the question as to whether or not such elections are beneficial. This paper distinguishes between the forces leading to long term decay and those hastening immediate breakdown, arguing that...

Using a new dataset of roll-call votes from the Mexican Congress, we explore the transformation of that country's legislative party system. Analyzing ideal points, dimensionality, and party cohesion, We show how after the fall of the ruling PRI, the ideological space shifted from cleavages on...

This paper introduces a naive Bayes classifier to detect electoral fraud using digit patterns in vote counts with authentic and synthetic data. The procedure is the following: (1) we create 10,000 simulated electoral contests between two parties using Monte Carlo methods. This training set is...