scholarly journals Brazilian Presidential Elections: Analysing Voting Patterns in Time and Space Using a Simple Data Science Pipeline

2020 ◽  
Author(s):  
Lucas Henrique Mantovani Jacintho ◽  
Tiago Pinho Da Silva ◽  
Antonio Rafael Sabino Parmezan ◽  
Gustavo Enrique de Almeida Prado Alves Batista
Keyword(s):  
Presidential Election ◽  
Voting Behavior ◽  
Presidential Elections ◽  
Data Science ◽  
First Year ◽  
Behavior Understanding ◽  
Analysis Process ◽  
Short And Long Term ◽  
Election Results ◽  
Political Economic

Since 1989, the first year of the democratic presidential election after a long period of a dictatorship regime, Brazil conducted eight presidential elections. This period was marked by short and long-term shifts of power and two impeachment processes. Such instability is a case of study in electoral studies, e.g., the study of the population voting behavior. Understanding patterns in the population behavior can give us insight into factors and influences that affect the quality of democratic political decisions. In light of this, our paper focuses on analyzing the Brazilian presidential election voting behavior across the years and the Brazilian territory. Following a data science pipeline, we divided the analysis process into five steps: (i) data selection; (ii) data preprocessing; (iii) identification of spatial patterns, in which we seek to understand the role of space in the election results using spatial autocorrelation techniques; (iv) identification of temporal patterns, where we investigate similar trends of votes over the years using a hierarchical clustering method; and (v) evaluation of the results. It is noteworthy that the data in this work represents the election results at the municipal level, from 1994 to 2018, of the two most relevant parties of this period: the Brazilian Social Democracy Party (PSDB) and the Workers’ Party (PT). Through the results obtained, we found the existence of spatial dependence in every electoral year investigated. Moreover, despite the changes in the political-economic context over the years, neighboring cities seem to present similar voting behavior trends.

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

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
L. H. M. Jacintho ◽  
T. P. da Silva ◽  
A. R. S. Parmezan ◽  
G. E. A. P. A. Batista
Keyword(s):  
Voting Behavior ◽  
Presidential Elections ◽  
Data Science ◽  
The Political ◽  
First Year ◽  
Left Wing ◽  
Spatio Temporal ◽  
Election Results ◽  
Political Spectrum ◽  
The Right

Since 1989, the first year of the democratic presidential election after a long period of a dictatorship regime, Brazil conducted eight presidential elections. Short and long-term shifts of power and two impeachment processes marked such a period. This instability is a research case in electoral studies, mainly regarding the understanding of citizens' voting behavior. Comprehending patterns in the population behavior can give us insight into phenomena and processes that affect democratic political decisions. In light of this, our paper analyses Brazilian electoral data at the municipal level from 1998 to 2018 using a simple data science pipeline, which consists of five steps: (i) data selection; (ii) data preprocessing; (iii) identification of spatial patterns, in which we seek to understand the role of space in the election results employing spatial auto-correlation techniques; (iv) identification of temporal patterns, where we investigate similar trends of votes over the years applying a hierarchical clustering method; and (v) evaluation of results. We study the presidential elections focusing on the right and left-wing parties most relevant for the period: the Brazilian Social Democracy Party~(PSDB) and the Workers' Party~(PT). We also analyse the congressman election data regarding parties ideologically to the right and left in the political spectrum. Through the obtained results, we found the existence of spatial dependence in every electoral year investigated. Moreover, despite the changes in the political-economic context over the years, neighboring cities seem to present similar voting behavior trends.

scholarly journals PREDICTION FOR THE 2012 UNITED STATES PRESIDENTIAL ELECTION USING MULTIPLE REGRESSION MODEL

2012 ◽  
Vol 6 (2) ◽  
pp. 77-97
Author(s):  
Pankaj Sinha ◽  
Aastha Sharma Aastha Sharma ◽  
Harsh Vardhan Singh
Keyword(s):  
Regression Model ◽  
Unemployment Rate ◽  
Presidential Election ◽  
Voting Behavior ◽  
Presidential Elections ◽  
Multiple Regression Model ◽  
Economic Factors ◽  
Gdp Growth Rate ◽  
Proposed Model ◽  
Midterm Elections

This paper investigates the factors responsible for predicting 2012 U.S. Presidential election. Though contemporary discussions on Presidential election mention that unemployment rate will be a deciding factor in this election, it is found that unemployment rate is not significant for predicting the forthcoming Presidential election. Except GDP growth rate, various other economic factors like interest rate, inflation, public debt, change in oil and gold prices, budget deficit/surplus and exchange rate are also not significant for predicting the U.S. Presidential election outcome. Lewis-Beck and Rice (1982) proposed Gallup rating, obtained in June of the election year, as a significant indicator for forecasting the Presidential election. However, the present study finds that even though there exists a relationship between June Gallup rating and incumbent vote share in the Presidential election, the Gallup rating cannot be used as the sole indicator of the Presidential elections. Various other non-economic factors like scandals linked to the incumbent President and the performance of the two parties in the midterm elections are found to be significant. We study the influence of the above economic and non-economic variables on voting behavior in U.S. Presidential elections and develop a suitable regression model for predicting the 2012 U.S. Presidential election. The emergence of new non-economic factors reflects the changing dynamics of U.S. Presidential election outcomes. The proposed model forecasts that the Democrat candidate Mr. Barack Obama is likely to get a vote percentage between 51.818 % - 54.239 %, with 95% confidence interval.

Nature of Tweets in the 2015 Nigerian Presidential Elections

2015 ◽  
Vol 2 (2) ◽  
pp. 34-52 ◽  
Author(s):  
Nwachukwu Andrew Egbunike ◽  
Noel Ihebuzor ◽  
Ngozi Onyechi
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Presidential Election ◽  
Social Engagement ◽  
Presidential Elections ◽  
Hate Speech ◽  
Political Mobilization ◽  
Election Results

Social media is becoming increasingly important as a means for social engagement. In Nigeria, Twitter is employed to convey opinion and make commentary on matters ranging from football to politics. Tweets are also used to inform, advocate, recruit and even incite. Previous studies have shown that Twitter could be effective for political mobilization. However, there is dearth of research on how Twitter has been used as a purveyor of neutral and/or hate speech in the Nigerian context. This study examined the nature of tweets in the immediate aftermath of the 2015 presidential election in Nigeria. The authors employed content analysis of 250 purposively selected tweets from the #Igbo hashtag which trended between March 29 and 31, 2015. The tweets were then categorized into five explicit hate and one neutral tweet category respectively. Results revealed the dominance of three hate tweet types: derogatory, mocking and blaming. These findings were then discussed bearing in mind earlier theories on the functionality of tweets and voting patterns from an analysis of the election results.

Recent Voting Behavior of Some Nationality Groups

1946 ◽  
Vol 40 (3) ◽  
pp. 528-532 ◽  
Author(s):  
Frederick W. Williams
Keyword(s):  
New York ◽  
New York City ◽  
Political Behavior ◽  
Census Tract ◽  
Voting Behavior ◽  
Presidential Elections ◽  
Foreign Born ◽  
Election Results ◽  
Total Stock

In continuation of a previous study, the rôle of some nationality groups in the last three presidential elections has been investigated. Whereas the previous study was based upon political behavior by counties within eight states, the present work is based upon political behavior by wards within four cities. The cities were chosen because they contained large proportions of certain nationality groups, and because in these cities it was possible to order census tract material from the 1940 census by wards. Only four cities (Buffalo, Chicago, Detroit, and Pittsburgh) were examined because of limitations of time and expense. New York City is not included because of appreciable changes in the boundaries of Assembly districts between elections.In order that a group be amenable to our procedure, it was necessary that there be proportionately great enough concentrations within wards so that the actual voting behavior of the group could possibly induce a shift in the election results. In this respect, it must be remembered that the proportion of foreign-born is usually about one-third of the total stock of any given group in the localities. Of the fourteen nationality groups studied here, therefore, not every one could be tested by our method.

Confronting Political—Economic Theories of Voting with Evidence

2001 ◽  
Vol 9 (4) ◽  
pp. 362-378 ◽  
Author(s):  
Robert Grafstein ◽  
Ann Moser
Keyword(s):  
Discrete Choice ◽  
Presidential Election ◽  
Voting Behavior ◽  
Competitive Equilibrium ◽  
Economic Interests ◽  
Economic Theories ◽  
Political Interests ◽  
Estimation Problems ◽  
Political Economic ◽  
The Impact

This paper illustrates one strategy for testing a theory of economic influences on voting. We use a competitive equilibrium model of the economy to determine the impact of an individual's economic position on his or her economic interests and, ultimately, political interests. We then test whether this impact is observed in voting behavior, addressing the resulting specification and estimation problems in the context of U.S. presidential election data. Our empirical results suggest that, despite these formidable problems, we can usefully connect political-economic models and discrete-choice (probit) models of voting.

Aggregate Economic Variables and Votes for Congress: A Rejoinder

1975 ◽  
Vol 69 (4) ◽  
pp. 1266-1269 ◽  
Author(s):  
Francisco Arcelus ◽  
Allan H. Meltzer
Keyword(s):  
Unemployment Rate ◽  
Voting Behavior ◽  
Presidential Elections ◽  
Inflation Rate ◽  
Real Income ◽  
Implicit Theory ◽  
Economic Variables ◽  
Econometric Evidence ◽  
Election Results

Our interest in the effect of aggregate economic variables on election results began in 1970 following a conversation with an administration official that we have reported elsewhere. We doubted both the implicit theory of voting behavior and the ability of the administration to achieve rates of inflation and unemployment even close to the ranges mentioned. We take this opportunity to note that the unemployment rate was higher and the inflation rate substantially higher than the adviser's estimate, but President Nixon was reelected.At the time, the principal econometric evidence of the effects of aggregate economic variables was a study by Kramer. Kramer found evidence of an effect of real income, but despite (or perhaps because of) the flaws in his procedure, he found no evidence of an effect of inflation or unemployment. Furthermore, then and now, most of the reported evidence pertains to congressional not presidential elections and to votes for congressmen, not seats in the Congress.

scholarly journals Fundamentals-Based State-Level Forecasts of the 2020 US Presidential Election

2020 ◽  
Author(s):  
Clemens Nollenberger ◽  
Gina-Maria Unger
Keyword(s):  
Presidential Election ◽  
Presidential Elections ◽  
National Level ◽  
State Level ◽  
Electoral College ◽  
Donald Trump ◽  
Improve Accuracy ◽  
Short And Long Term ◽  
Us Presidential Election

Forecasts of US presidential elections have gained considerable attention in recent years. However, as became evident in 2016 with the victory of Donald Trump, most of them consider presidential elections only at the national level, neglecting that these are ultimately decided by the Electoral College. In order to improve accuracy, we believe that forecasts should instead address outcomes at the state-level to determine the eventual Electoral College winner. We develop a political economy model of the incumbent vote share across states based on different short- and long-term predictors, referring up to the end of the second quarter of election years. Testing it against election outcomes since 1980, our model correctly predicts the eventual election winner in 9 out of 10 cases – including 2016 –, with the 2000 election being the exception. For the 2020 election, it expects Trump to lose the Electoral College, as only 6.2 percent of simulated outcomes cross the required threshold of 270 Electoral Votes, with a mean prediction of 106 Electoral Votes.

scholarly journals A Bayesian Approach for Validation of Election Results

2020 ◽  
Vol 27 (2) ◽  
pp. 22-31
Author(s):  
R.K. Ogundeji ◽  
J.N. Onyeka-Ubaka
Keyword(s):  
Political Parties ◽  
Bayesian Approach ◽  
Bayesian Methods ◽  
Presidential Election ◽  
Presidential Elections ◽  
Empirical Bayes ◽  
Posterior Probability ◽  
Election Process ◽  
Credible Intervals ◽  
Election Results

Election process and results in many countries have resulted in both political and economic instability of that country. Fair and credible election process and results must be evidence-based and statistical proven. This study employed a Bayesian procedure for the validation of election results. Based on Nigerian 2011 and 2015 presidential election results, Bayesian credible intervals were obtained to assess the credibility of Nigeria presidential election results. The study explores Bayesian methods using a Bayesian model called beta-binomial conjugate model to compute posterior probability of electoral votes cast and confirm if these votes are within Bayesian credible intervals. The results obtained showed that election outcomes for the two major political parties in Nigeria 2011 presidential election are not within Bayesian credible bounds while 2015 presidential election results are within computed Bayesian credible bounds. Also, in contrast to frequentist approach, applied Bayesian methodology exhibited smaller variance which is an indication that Bayesian approach is more efficient. Thus, for election to be fair, credible and acceptable by the electorates, Bayesian approach can be used to validate electoral process and results. Keywords: Bayesian Methods, Bayesian Credible Intervals, Beta-Binomial Model, Empirical Bayes, Nigeria Presidential Elections.

scholarly journals Inferring the votes in a new political landscape. The case of the 2019 Spanish Presidential elections.

2020 ◽  
Author(s):  
Didier Grimaldi ◽  
Javier Diaz ◽  
Hugo Arboleda
Keyword(s):  
Presidential Election ◽  
Online Social Networks ◽  
Presidential Elections ◽  
Research Topic ◽  
Machine Learning Algorithms ◽  
The Past ◽  
Political Landscape ◽  
Research Institutes ◽  
Twitter Data ◽  
Election Results

Abstract The avalanche of personal and social data circulating in Online Social Networks over the past 10 years has attracted a great deal of interest from Scholars and Practitioners who seek to analyse not only their value, but also their limits. Predicting election results using Twitter data is an example of how data can directly influence the politic domain and it also serves an appealing research topic. This article aims to predict the results of the 2019 Spanish Presidential election and the voting share of each candidate, using Tweeter. The method combines sentiment analysis and volume information and compares the performance of five Machine Learning algorithms. Several data scrutiny uncertainties arose that hindered the prediction of the outcome. Consequently, the method develops a political lexicon-based framework to measure the sentiments of online users. Indeed, an accurate understanding of the contextual content of the tweets posted was vital in this work. Our results correctly ranked the candidates and determined the winner by means of a better prediction of votes than official research institutes.

scholarly journals Charismatic and Affective Rhetoric in a Presidential Campaign

2014 ◽  
pp. 120-137
Author(s):  
Sheilesha R. Willis ◽  
Gloria L. Sweida ◽  
Stephanie Glassburn ◽  
Cynthia L. Sherman ◽  
Michelle C. Bligh
Keyword(s):  
Content Analysis ◽  
Presidential Election ◽  
Voting Behavior ◽  
Presidential Elections ◽  
Presidential Campaign ◽  
2008 Presidential Election ◽  
Presidential Candidates ◽  
Emotional Language ◽  
Democratic Parties

Although prior research demonstrates that charisma and rhetoric are two determinants of voting behavior, few studies have examined the effects of charismatic rhetoric and affect as they pertain to the outcomes of presidential elections. Using DICTION software for content analysis, 432 pre-convention speeches from the 2008 presidential election were analyzed to explore the effects that charismatic rhetoric and affect have on presidential candidates’ success. Results indicate that there were more similarities than differences in the charismatic and affect-laden rhetoric of successful and unsuccessful presidential candidates in both the Republican and Democratic parties. Overall, the results demonstrate that both successful and unsuccessful presidential candidates used charismatic rhetoric and emotional language to motivate their followers in the 2008 presidential election.

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