Coded Language: The History, the Message, and 2016

How do politicians, particularly presidential candidates, talk about race without talking about race? Since the 1960s, race baiting in American politics has gone increasingly underground into the realm of coded language and dog-whistle rhetoric; that was until 2016 when the election of Donald Trump brought much of this conversation from the covert and into the over. The old codes were not gone, but they seemingly meant less. Through an examination of campaign ads and convention speeches from the elections of 1968, 1988, and 2008, this paper explores the history of coded language to provide a partial explanation of what made President Trump\u27s rhetoric so powerful. This paper incorporates two intermediate theses to illustrate its ultimate thesis. First, that as times change race baiting language must also change in order to incite the greatest following from backlash voters. Second, that this language must occur alongside social turmoil and anxiety amongst the backlash electorate. These two theses come together to generate an ultimate thesis that Trump took years of coded practices, broke many of them, and played to backlash voters fears of outsiders, particularly Muslims and Latinos

clicktatorship and democrazy: Social media and political campaigning

This chapter aims to direct attention to the political dimension of the social media age. Although current events like the Cambridge Analytica data breach managed to raise awareness for the issue, the systematically organized and orchestrated mechanisms at play still remain oblivious to most. Next to dangerous monopoly-tendencies among the powerful players on the market, reliance on automated algorithms in dealing with content seems to enable large-scale manipulation that is applied for economical and political purposes alike. The successful replacement of traditional parties by movements based on personality cults around marketable young faces like Emmanuel Macron or Austria’s Sebastian Kurz is strongly linked to products and services offered by an industry that simply provides likes and followers for cash. Inspired by Trump’s monopolization of the Twitter-channel, these new political acteurs use the potential of social media for effective message control, allowing them to avoid confrontations with professional journalists. In addition, an extremely active minority of organized agitators relies on the viral potential of the web to strongly influence and dictate public discourse – suggesting a shift from the Spiral of Silence to the dangerous illusion of a Nexus of Noise

Measuring relative opinion from location-based social media: A case study of the 2016 U.S. presidential election

Social media has become an emerging alternative to opinion polls for public opinion collection, while it is still posing many challenges as a passive data source, such as structurelessness, quantifiability, and representativeness. Social media data with geotags provide new opportunities to unveil the geographic locations of users expressing their opinions. This paper aims to answer two questions: 1) whether quantifiable measurement of public opinion can be obtained from social media and 2) whether it can produce better or complementary measures compared to opinion polls. This research proposes a novel approach to measure the relative opinion of Twitter users towards public issues in order to accommodate more complex opinion structures and take advantage of the geography pertaining to the public issues. To ensure that this new measure is technically feasible, a modeling framework is developed including building a training dataset by adopting a state-of-the-art approach and devising a new deep learning method called Opinion-Oriented Word Embedding. With a case study of the tweets selected for the 2016 U.S. presidential election, we demonstrate the predictive superiority of our relative opinion approach and we show how it can aid visual analytics and support opinion predictions. Although the relative opinion measure is proved to be more robust compared to polling, our study also suggests that the former can advantageously complement the later in opinion prediction

The far-right’s influence on Twitter during the 2018 Andalusian elections: an approach through political leaders

New technologies allow politicians to spread their messages omitting the role of mediators. In this context, the Internet has also promoted the emergence of a new actor, digital opinion leaders, who go beyond traditional politics and seek to set the public agenda. One of the main questions nowadays is whether social media, and in particular Twitter as a consolidated tool for political communication, is only used as a sounding board for their political statements, spurring the messages of populist forces. With this in mind, the main objective of this research is to explore the influence of the far-right in the public debate of political leaders on Twitter, analyzing the specific case of the Andalusian regional elections held in December 2018. These elections can be considered a political turning point, with an extreme right party winning seats in a Spanish regional election for the first time in 35 years. In this paper we analyze if Vox used a differentiated strategy via this social network compared to the candidates of the traditional parties: PSOE, PP, Ciudadanos, and Adelante Andalucía. Using content analysis on Twitter as a method, this research determines how Vox candidates worked as influencers of the digital political debate, despite being extra-parliamentary. Vox marked the agenda for the rest of the leaders, while generating great expectation among the audience

Illuminating an Ecosystem of Partisan Websites

This paper aims to shed light on alternative news media ecosystems that are believed to have influenced opinions and beliefs by false and/or biased news reporting during the 2016 US Presidential Elections. We examine a large, professionally curated list of 668 hyper-partisan websites and their corresponding Facebook pages, and identify key characteristics that mediate the traffic flow within this ecosystem. We uncover a pattern of new websites being established in the run up to the elections, and abandoned after. Such websites form an ecosystem, creating links from one website to another, and by `liking' each others' Facebook pages. These practices are highly effective in directing user traffic internally within the ecosystem in a highly partisan manner, with right-leaning sites linking to and liking other right-leaning sites and similarly left-leaning sites linking to other sites on the left, thus forming a filter bubble amongst news producers similar to the filter bubble which has been widely observed among consumers of partisan news. Whereas there is activity along both left- and right-leaning sites, right-leaning sites are more evolved, accounting for a disproportionate number of abandoned websites and partisan internal links. We also examine demographic characteristics of consumers of hyper-partisan news and find that some of the more populous demographic groups in the US tend to be consumers of more right-leaning sites.Comment: Published at The Web Conference 2018 (WWW 2018). Please cite the WWW versio

Validation of Twitter opinion trends with national polling aggregates: Hillary Clinton vs Donald Trump

Measuring and forecasting opinion trends from real-time social media is a long-standing goal of big-data analytics. Despite its importance, there has been no conclusive scientific evidence so far that social media activity can capture the opinion of the general population. Here we develop a method to infer the opinion of Twitter users regarding the candidates of the 2016 US Presidential Election by using a combination of statistical physics of complex networks and machine learning based on hashtags co-occurrence to develop an in-domain training set approaching 1 million tweets. We investigate the social networks formed by the interactions among millions of Twitter users and infer the support of each user to the presidential candidates. The resulting Twitter trends follow the New York Times National Polling Average, which represents an aggregate of hundreds of independent traditional polls, with remarkable accuracy. Moreover, the Twitter opinion trend precedes the aggregated NYT polls by 10 days, showing that Twitter can be an early signal of global opinion trends. Our analytics unleash the power of Twitter to uncover social trends from elections, brands to political movements, and at a fraction of the cost of national polls

Identity crisis: how ideological and rhetorical failures cost Egyptians their revolution

Thesis (M.A.) University of Alaska Fairbanks, 2019The Egyptian uprising, which began on January 25, 2011, and ended on February 11, 2011, culminated in the ending of President Hosni Mubarak's 30-year reign as dictator. After free elections in which the Muslim Brotherhood ascended to power in the country, they were ousted in a military coup d'état only one year after their ascension to power and were replaced by former military general Abdul-Fattah el-Sisi. The symptoms which led the country to rise up against Mubarak continue to exist under el-Sisi today, indicating that no revolution really took place. This paper answers the question, "why did the revolution fail?", offering a rhetorical reason for the revolution's failure. The uprisings, which were billed as decentralized, offer unique opportunities for analysis of rhetorical strategy. This paper uses the reconstitutive-discourse model, a critical model which examines a rhetor's reconstitution of their audience's character, to examine the rhetoric of three different parties in the revolution. First, it examines the rhetoric of all protestors irrespective of source via Twitter and on the ground protestors; next it looks at the rhetoric of Wael Ghonim, who is credited with instigating the uprisings, and Mohammed ElBaradei, an influential figure who became interim vice-president in the aftermath of the uprisings. The study found that first, the uprisings were not really decentralized and indeed has leaders. Further, rhetorical failures on the part of its leaders caused the uprisings to fail in their goal of democratic revolution