A data-driven network approach for characterization of political parties’ ideology dynamics

Abstract

Political ideology is a major social phenomena that plays a crucial role in the formation and dynamics of ideologically-aligned social groups. This alignment gives rise to some of the most powerful social structures in modern democracies, the political parties. Due to the influence and importance of political parties in society, estimating their ideology is an active topic in political science research. However ideology is a very subjective phenomena and existing quantitative methods for ideology estimation are susceptible to a variety estimation issues, specially when applied in multi-partisan systems. In this work, we developed a data-driven network model for political ideology estimation based on partisan relationships established from party-switching politicians. The model is applied to the Brazilian case and yields results consistent with existing literature in the Brazilian political scenario while addressing data scarcity issues in existing methodologies.

Detecting coalitions by optimally partitioning signed networks of political collaboration

“…We propose a general method for identifying cohesive groups in signed networks (networks with positive and negative edges), and apply it to political networks, which have become a common focus in complex network analysis [1][2][3] . Specifically, we examine signed networks of political collaboration and opposition to identify the members of polarized coalitions in the US Congress, then use these coalitions to examine the impact of polarization on effectiveness in passing bills.…”

Analysing Spatio-Temporal Voting Patterns in Brazilian Elections Through a Simple Data Science Pipeline

“…In recent years, however, we have witnessed an increased interest in analyzing the outcomes of elections worldwide due to advancements in technologies that allow easy access to electoral data [Norris and Grömping 2019]. Thereby, researchers from the statistics and social science communities have contributed to several aspects of voting behavior analysis, such as understanding external factors that may influence electoral results [Hernández and León 2020;Okunev et al 2020;Reid and Liu 2019], the study of the role of space in elections [Mota 2019;Mansley and Demšar 2015], the analysis of ideological trends [Zucco and Power 2020;Faustino et al 2019;Power and Rodrigues-Silveira 2019], and the voting behavior on social media [Recuero et al 2020;Praciano et al 2018]. This article focuses on understanding the role of space and time in Brazilian elections.…”

Roots of dissent: Trade liberalization and the rise of populism in Brazil

“…Symmetrically, the parties considered as right-wing are those with an ideological score similar or further to the right than the PSL in 2018 (Bolsonaro's party) in the period 2002-18. 15 Ideological scores were compiled from Faustino et al (2019), who consider the evolution of parties ideologies through time to measure their position in the left-right continuum. Figure 3 shows changes in voters' preferences from right to left in the time preceding the 2002 election of Lula and changes from left to right over the time period before the 2018 election of Bolsonaro.…”

“…To capture this complexity, we first considered only votes obtained by parties in the first election round to ensure that all states were included in our calculation, and not just the states which had to undergo a second round of elections (in several states decisions were made during the first round). Second, to assign parties to the political left or the political right, we made use of an ideological score calculated by Faustino et al (2019), which updates and enriches a previous score calculated by Power and Zucco (2009). We considered as left-wing parties all those parties reporting an ideological score similar or more to the left than the PT (Lula's party) in 2002.…”