Argentinian Elections

Election forecasts, based on public opinion polls or statistical structural models, regularly appear before national elections in established democracies around the world. However, in less established democratic systems, such as those in Latin America, scientific election forecasting by opinion polls is irregular and by statistical models is almost non-existent. Here we attempt to ameliorate this situation by exploring the leading case of Argentina, where democratic elections have prevailed for the last thirty-eight years. We demonstrate the strengths—and the weaknesses—of the two approaches, finally giving the nod to structural models based political and economic fundamentals. Investigating the presidential and legislative elections there, 1983 to 2019, our political economy model performs rather better than the more popular vote intention method from polling.

Choosing the Lesser Evil: Forecasting Presidential Elections in Peru

The Peruvian political landscape is dominated by the weakness of party organizations, the continuous rotation of political personalities, and, in turn, high electoral volatility and uncertainty. Nevertheless, we observe patterns of electoral competition that suggest candidates learn to capture the political center and compete over the continuation of an economic model that has sustained growth. We use this information to record the vote intention for the candidate viewed as the lesser evil. Our forecasting results predict a good share of the variation in political support for this candidate. The out-of-sample prediction also comes fairly close to the real electoral results. These findings provide some degree of electoral certainty in an area that, to date, remains understudied.

A matter of representation: Populism and the pandemic in Italy

This chapter deals with how populist parties reacted and engaged with the pandemic in Italy, one of the European countries most affected by the spread of the SARS-CoV-2 virus. The main argument of this chapter is that populist actors are successful in profiting from a crisis when they can credibly frame it as a failure of representation. The case of Italy, which has been defined as a “country of many populisms” (Tarchi 2008), is particularly insightful. Since the outset of the pandemic at the end of February of 2020, there were two populist parties in the system , both on the right of the political spectrum: the League (former Northern League) and Brothers of Italy. After a first period known as “rally around the flag” the two parties' strategy was somehow similar until they started to diverge substantially in February 2021. In general terms, we can say that—until the breakdown of the second Conte government—the League discursively attacked the government on managing the pandemic, focusing mainly on two issues: migration and the economy. When the League entered the government, supporting Mario Draghi’s cabinet, its discourse changed even if its loyalty to the government has been flaky, at least. This strategy of keeping one foot in and one out of government (see Albertazzi and McDonnell 2005) has always been a trademark characteristic of the (Northern) League since the 1990s. Conversely, Brothers of Italy, while sharing with the League the critique to the government supported by the Democratic Party and the Five Star Movement during the first year, has later changed its strategy becoming the only relevant party in opposition to Mario Draghi’s government. This allowed FdI to systematically challenge the government's actions and depict itself as the only party to act in the interest of the people, opposing to the elite. Even if the pandemic is still unfolding, vote intention shows that Brothers of Italy has become the first Italian party, demonstrating to have taken advantage of the crisis, through a framing that was more functional with its populist appeal and in turn resulted more credible to voters.

Politically Invisible in America

ABSTRACT Campaigns, parties, interest groups, pollsters, and political scientists rely on voter-registration lists and consumer files to identify people as targets for registration drives, persuasion, and mobilization and to be included in sampling frames for surveys. We introduce a new category of Americans: the politically invisible—that is, people who are unreachable using these voter and marketing lists. Matching a high-quality, random sample of the US population to multiple lists reveals that at least 11% of the adult citizenry is unlisted. An additional 12% is mislisted (i.e., not living at their recorded address). These groups are invisible to list-based campaigns and research, making them difficult or impossible to contact. Two in five Blacks and (citizen) Hispanics are unreachable, but only 18% of whites. The unreachable are poorer than the reachable population, have markedly lower levels of political engagement, and are much less likely to report contact with candidates and campaigns. They are heavily Democratic in party identification and vote intention, favoring Obama versus Romney 73 to 27, with only 16% identifying as Republicans. That the politically invisible are more liberal and from historically marginalized groups shows that the turn to list-based campaigning and research could worsen existing biases in the political system.

Proposta de um modelo para predição do resultado das eleições presidenciais brasileiras baseado em técnicas de regressão

Prediction of elections is a subject that excites the population, especially in the last few months before an election. In Brazil, there is a wide availability of political, economic and social data, in institutions such as TSE, IBGE and opinion research institutes that can be used as sources to create prediction models. Therefore, this work aims to build multivariate linear regression and regression tree models to predict the percentage of votes received by the situational candidate for the presidency of Brazil. The multivariate linear regression model had the smallest prediction errors, with MAE of 1.45 in the first round and 1.48 in the second, with margins smaller than 1\% in 2002, 2006 and 2018. The proposed models seemed to be more accurate than other models found in the literature. As main contributions, it was possible to observe that the sampling of data by state and the use of the illiteracy rate and the popular vote intention contributed directly to the performance of the models.

The Effectiveness of Political Campaign on Instagram to Influence Vote Intention

This study is conducted effectiveness of political campaign through Instagram as a social media to influence vote intention among Millenials in Indonesia. The study is performed with a quantitative approach and gathered data from 99 respondents that is a citizen of Bandung and eligible to vote. The findings revealed that four variables that influence the quality of the social media political campaign, namely content quality, the informality of speech, design, and frequency of post have the significant and positive influence to vote intention. However, among these variables, the most significant and positive influence belongs to design. It seems related to the nature of Instagram as photo-based social media.

Exploring the Role of Media Use Within an Integrated Behavioral Model (IBM) Approach to Vote Likelihood

Political interest is a key predictor of likelihood to vote. We argue that the political interest–vote intention relationship can be explained by well-established theories that predict behavior across domains (e.g., theory of reasoned action, theory of planned behavior). Relying on the integrated behavioral model, we propose a core mediation model with vote likelihood (i.e., behavioral intention) as the dependent variable. Two types of media use (conservative and liberal–moderate) are then assessed in relation to the core model. We explore the ways in which our results contribute to theory and outline a research agenda.

NetVote: A Strict-Coercion Resistance Re-Voting Based Internet Voting Scheme with Linear Filtering

This paper proposes NetVote, an internet voting protocol where usability and ease in deployment are a priority. We introduce the notion of strict coercion resistance, to distinguish between vote-buying and coercion resistance. We propose a protocol with ballot secrecy, practical everlasting privacy, verifiability and strict coercion resistance in the re-voting setting. Coercion is mitigated via a random dummy vote padding strategy to hide voting patterns and make re-voting deniable. This allows us to build a filtering phase with linear complexity, based on zero knowledge proofs to ensure correctness while maintaining privacy of the process. Voting tokens are formed by anonymous credentials and pseudorandom identifiers, achieving practical everlasting privacy, where even if dealing with a future computationally unbounded adversary, vote intention is still hidden. It is not assumed for voters to own cryptographic keys prior to the election, nor store cryptographic material during the election. This property allows voters not only to vote multiple times, but also from different devices each time, granting the voter a vote-from-anywhere experience. This paper builds on top of the paper published in CISIS’19. In this version, we modify the filtering. Moreover, we formally define the padding technique, which allows us to perform the linear filtering scheme. Similarly we provide more details on the protocol itself and include a section of the security analysis, where we include the formal definitions of strict coercion resistance and a game based definition of practical everlasting privacy. Finally, we prove that NetVote satisfies them all.