Browsing by Subject "political science"

Now showing 1 - 3 of 3
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    A Case of Misunderstood Identity: The Role of Rural Identity in Contemporary American Mass Politics
    (2021-08) Lunz Trujillo, Kristin
    Why do rural individuals tend to be more right-wing in the contemporary U.S.? I answer this question by treating rurality as a social identity – a psychological attachment to rural or small-town life that encompasses a particular set of values and worldview. Previous studies on rural identity by scholars such as Katherine Cramer or Arlie Hochschild argue that rural areas’ turn to the right – particularly to right-wing populism - is rooted in socioeconomic class-based concerns and anti-urban resentment. However, using national experimental and survey data, in contrast to the qualitative and ethnographic approaches typically used, I find that rural identifiers are not more likely to be lower- or working-class individuals or to express economic concerns. Further, rural social identity does not significantly differ between racial and ethnic groups in the U.S. In other words, politically speaking the white working class does not equal rural identity, something often and nearly automatically assumed in scholarly and popular accounts. Instead, I argue that the turn to the right has been due to rural identifiers’ intermediate status in the societal status hierarchy. Rural areas perceive a group status-based threat from two different out-groups, which map onto definitions of right-wing populism. The first out-group is experts and intellectuals, who rural residents believe favor lower-status groups, such as immigrants – a second out-group - allowing them to cut in line ahead of rural Americans to gain social, economic and political status. These two out-groups (intellectuals/experts and immigrants) are more likely to be urban residents but not necessarily, complicating the idea of anti-urban resentment being the primary feature of rural identity. In this work, I rely on several sources of quantitative data, including original survey data and experiments collected over three years, as well as data from the ANES (American National Election Studies), the CCES (Cooperative Congressional Election Studies), and county-level data.
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    Influence of Gossip Media on Political Attitudes of Various Thinkers
    (2015-05-29) Yushchenko, Yekaterina; Miller, Joanne
    This study sought to look at how people of different levels of need for cognition are influenced by hidden political messages in gossip media. Results were collected by testing college students on their opinions on gun control and crime related issues before and after consuming a piece of biased gossip media, nonbiased gossip (control) media, and biased news media. This study found that high need for cognition people were influenced by biased media significantly more than those low in need for cognition. Despite the frivolous appearance of gossip media, this study found that both gossip and news media were significant influencers of opinion, but only for high need for cognition individuals and on separate issues.
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    Quantifying Political Leaning from Tweets, Retweets, and Retweeters
    (IEEE Transactions on Knowledge and Data Engineering, 2016) Wong, Felix MFW; Tan, Chee Wei; Sen, Soumya; Chiang, Mung
    The widespread use of online social networks (OSNs) to disseminate information and exchange opinions, by the general public, news media and political actors alike, has enabled new avenues of research in computational political science. In this paper, we study the problem of quantifying and inferring the political leaning of Twitter users. We formulate political leaning inference as a convex optimization problem that incorporates two ideas: (a) users are consistent in their actions of tweeting and retweeting about political issues, and (b) similar users tend to be retweeted by similar audience. Then for evaluation and a numerical study, we apply our inference technique to 119 million election-related tweets collected in seven months during the 2012 U.S. presidential election campaign. Our technique achieves 94% accuracy and high rank correlation as compared with manually created labels. By studying the political leaning of 1,000 frequently retweeted sources, 230,000 ordinary users who retweeted them, and the hashtags used by these sources, our numerical study sheds light on the political demographics of the Twitter population, and the temporal dynamics of political polarization as events unfold.