Suchergebnisse

We examined the relationship between political affiliation, perceptual (percentage, slope) estimates, and subjective judgements of disease prevalence and mortality across three chart types. An online survey (N = 787) exposed separate groups of participants to charts displaying (a) COVID-19 data or (b) COVID-19 data labeled 'Influenza (Flu)'. Block 1 examined responses to cross-sectional mortality data (bar graphs, treemaps); results revealed that perceptual estimates comparing mortality in two countries were similar across political affiliations and chart types (all ps > .05), while subjective judgements revealed a disease x political party interaction ( p < .05). Although Democrats and Republicans provided similar proportion estimates, Democrats interpreted mortality to be higher than Republicans; Democrats also interpreted mortality to be higher for COVID-19 than Influenza. Block 2 examined responses to time series (line graphs); Democrats and Republicans estimated greater slopes for COVID-19 trend lines than Influenza lines ( p < .001); subjective judgements revealed a disease x political party interaction ( p < .05). Democrats and Republicans indicated similar subjective rates of change for COVID-19 trends, and Democrats indicated lower subjective rates of change for Influenza than in any other condition. Thus, while Democrats and Republicans saw the graphs similarly in terms of percentages and line slopes, their subjective interpretations diverged. While we may see graphs of infectious disease data similarly from a purely mathematical or geometric perspective, our political affiliations may moderate how we subjectively interpret the data.

By the evolvement in technology, the way of expressing opinions switched direction to the digital world. The domain of politics, as one of the hottest topics of opinion mining research, merged together with the behavior analysis for affiliation determination in texts, which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 were constituted by Linguistic Inquiry and Word Count (LIWC) features were tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that the "Decision Tree", "Rule Induction" and "M5 Rule" classifiers when used with "SVM" and "IGR" feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature "Function", as an aggregate feature of the linguistic category, was found as the most differentiating feature among the 68 features with the accuracy of 81% in classifying articles either as Republican or Democrat.

This paper studies the impact of confirmation bias on the choice between biased sources of political information in a pre-election period. A sample of 204 Portuguese respondents was used, through a survey regarding their political identity and relating it to each one's choice of information sources, as a voter and as a single decision-maker. Significant differences in behaviour were found according to one's political identity. Evidence was found for some significant confirmation-seeking behaviour among right-wing participants, but some hypotheses concerning expressive voting and the effects of various factors on confirmation bias weren't confirmed.

Renewable energy is often presented as a partisan issue. However, solar incentives have made rooftop PV attractive to many consumers, regardless of political affiliation. This paper quantifies the role of political affiliation in rooftop PV adoption for the Democratic-leaning state of New York and Republican-leaning state of Texas. High resolution rooftop PV installation data from Google Project Sunroof is combined with election data from the Harvard Election Data Archive. We applied a bootstrapped LOWESS model to fit local linear relationships between rooftop PV adoption and both voting behavior and household income. In doing so, we find that Republican-majority communities are installing rooftop PV at equal or greater rates than Democraticmajority communities. While Republican politicians may be less likely than Democrats to support renewable energy, this partisan division is not found at the voter level.

I believe that there is a correlation between musical taste and political affiliation, based upon my experience in the church and as an observer of the congregation. By asking individual people -- such as choir directors, organists, and theologians -- about a correlation between political affiliation and liturgical music taste, I believe there is enough of a pattern to deserve study. This pattern I am looking for should exhibit some shared interest in the subject at hand, some examples of the congregation liking or not liking particular music, or further information that I can explore. After interviewing those workers of the Church, I will delve into the development of liturgical music across the ages, observing their connection to what my subjects have said. Finally I will examine the data and come up with a conclusion on the correlation between liturgical music and political affiliation.

Political identities are strongly associated with political tolerance. Specifically, previous research shows that American liberals report higher levels of tolerance toward marginalized groups than conservatives. Political orientation, however, varies more among Democrats than Republicans, which might mean that Democrats are relatively diverse in their levels of political tolerance. In this article, the authors ask how the association between political orientation and political tolerance varies across political parties. Using General Social Survey data, the authors find that tolerance is highest among liberals, followed by moderates and conservatives. Regression models with interactions between party and orientation demonstrate that political orientation is consequential for tolerance levels among independents, and especially Democrats, but is far less so for Republicans. Additional analyses demonstrate how the party-contingent association between political orientation and tolerance varies by the outgroup in question. This research demonstrates the complexity of political dimensions when considering support for the rights of marginalized outgroups.

The goal of this research is to examine the effect of presidential political affiliation on economic conditions in the US. Previous studies focus extensively on the effect of political affiliation on the stock market. We take a step further and focus on the economy more broadly by estimating the effect on stock market performance, real GDP, and the unemployment rate. We find that under Republican administrations, the change in real GDP is on average 2.97% lower than under Democratic administrations. However, we find no significant evidence of a correlation between presidential political affiliation and the unemployment rate or stock market performance. Our findings support findings from previous research and are important in showing how general views on the strong effect of partisan politics on the economy might be overstated.