Partisanship is a stable trait but expressions of partisan preferences can vary according to social context. When particular preferences become socially undesirable, some individuals refrain from expressing them in public, even in relatively anonymous settings such as surveys and polls. In this study, we rely on the psychological trait of self-monitoring to show that Americans who are more likely to adjust their behaviors to comply with social norms (i.e. high self-monitors) were less likely to express support for Donald Trump during the 2016 Presidential Election. In turn, as self-monitoring decreases, we find that the tendency to express support for Trump increases. This study suggests that - at least for some individuals - there may have...
The outcome of the 2016 U.S. Presidential election was a big surprise to many, as the majority of po...
Using data from the American National Election Studies, we investigated the relationship between cog...
The study attempts to develop an ordinal logistic regression model to identify the predictors of par...
Nonresponses to vote intention questions notoriously impact the quality of electoral predictions. Th...
Social norms, usually persistent, can change quickly when new public information arrives, such as a ...
In the lead up to the 2016 election, many commentators argued that Donald Trump’s personality and ac...
The outcome of the 2016 U.S. Presidential election was a big surprise to many, as the majority of po...
This study examines the role of traditional media-outlets when Donald Trump was elected the 45th pre...
American politics is becoming increasingly polarized, which biases decision-making and reduces open-...
Research in the wake of the contentious 2016 presidential primaries contends both Democrats and Repu...
American politics is becoming increasingly polarized, which biases decision-making and reduces open-...
Using focus groups, we examined support and opposition for Donald Trump prior to the 2016 presidenti...
In the context of Donald Trump’s 2016 election as President of the United States and a global rise i...
This two part analysis looks at forecasting models in the United States\u27 2016 presidential electi...
The outcome of the 2016 U.S. Presidential election was a big surprise to many, as the majority of po...
The outcome of the 2016 U.S. Presidential election was a big surprise to many, as the majority of po...
Using data from the American National Election Studies, we investigated the relationship between cog...
The study attempts to develop an ordinal logistic regression model to identify the predictors of par...
Nonresponses to vote intention questions notoriously impact the quality of electoral predictions. Th...
Social norms, usually persistent, can change quickly when new public information arrives, such as a ...
In the lead up to the 2016 election, many commentators argued that Donald Trump’s personality and ac...
The outcome of the 2016 U.S. Presidential election was a big surprise to many, as the majority of po...
This study examines the role of traditional media-outlets when Donald Trump was elected the 45th pre...
American politics is becoming increasingly polarized, which biases decision-making and reduces open-...
Research in the wake of the contentious 2016 presidential primaries contends both Democrats and Repu...
American politics is becoming increasingly polarized, which biases decision-making and reduces open-...
Using focus groups, we examined support and opposition for Donald Trump prior to the 2016 presidenti...
In the context of Donald Trump’s 2016 election as President of the United States and a global rise i...
This two part analysis looks at forecasting models in the United States\u27 2016 presidential electi...
The outcome of the 2016 U.S. Presidential election was a big surprise to many, as the majority of po...
The outcome of the 2016 U.S. Presidential election was a big surprise to many, as the majority of po...
Using data from the American National Election Studies, we investigated the relationship between cog...
The study attempts to develop an ordinal logistic regression model to identify the predictors of par...