This master's thesis deals with the implications of metaphorical language, which comedy news programs used to portray Donald Trump as a candidate during the 2016 US presidential election. First, the author outlines the most important moments of Donald Trump's presidential campaign, then introduces the comedy news genre as well as three comedy news programs - The Daily Show, Last Week Tonight and Real Time - which are included in the analytical part of the thesis. The thesis continues with the theoretical and methodological chapters, in which conceptual metaphor analysis based on the works of Lakoff, Johnson and Yanow is presented. The metaphor analysis itself, performed on 73 comedy news episodes, reveals that mostly the same metaphors were used across all three programs and they overwhelmingly portray Donald Trump as non-human. As the election kept approaching, Donald Trump was increasingly portrayed as "a natural disaster," "the apocalypse" or "the Devil." The author suggests that the overall tacit objective of the metaphors used in the three comedy news programs was to dehumanize Donald Trump. Finally, the limitations of the analysis are discussed and suggestions for further research on the implications of metaphorical language are made.

The aim of this thesis is to look for paralels in reactions and attitudes of Czech and American media towards offensive statements of presidents of the Czech Republic and USA with the focus on mainstream media. In a theoretical part of the thesis the role and function of media in liberal democracies are defined. Following part describes an actual media landscapes of USA and the Czech Republic. The main part - research, is based on the description of the media landscapes in both countries and analyzes the media reactions and attitudes towards one specific presidential statement (one by US president Donald Trump, one by Czech president Milos Zeman). Each statement had to be at most critical, attacking the media and had to raise high media response. Media reactions were afterwards analyzed using qualitative content analysis according to the principles of grounded theory. In the conclusion the categories given by the analysis are being compared and analyzed.

This diploma thesis examines the impact of the former US President Donald Trump's private Twitter account on agenda-building and how the Czech media work with information from this account. The diploma thesis is divided into two parts. The first part of the diploma thesis deals with the key theories and concepts of media studies such as the theory of agenda-setting, gatekeeping, news values, framing and intermedia agenda-setting. It also focuses on the contemporary form of political communication and the phenomenon of celebrity politics. The thesis also includes the overview of existing studies describing the political communication of the former US President Donald Trump on the social networking site Twitter and confirm the agenda-building role of this social network. The second part of the diploma thesis describes the research methodology and subsequent quantitative content analysis of news articles. The findings of quantitative content analysis are explained in the context of the theoretical concepts and previous studies. One of the main findings of this thesis is that Trump was able to some extent build media agenda, frame different topics and events and control his image in the media through his Twitter account.

The storming of the U.S. Capitol on January 6, 2021, came to shock the entire world. An angry mob of Trump supporters had, after months of encouragement from President Trump, attacked the heart of American democracy in an attempt to overturn the results of the 2020 presidential election. The attempt failed, when a new president, Joe Biden, was inaugurated on January 20, 2021. The aim of this case study is to create an understanding of how President Donald Trump, his administration and allied Republicans tried to overthrow American democracy in connection with the 2020 presidential election, and why they didn’t succeed. Using Steven Levitsky and Daniel Ziblatt's 2018 book “How Democracies Die” as the theoretical framework of the thesis, an ideal-type definition of “how to overthrow a democracy” was formed. Based on this ideal-type definition, the source material, consisting of documents, social media posts, newspaper reports and transcribed speeches, was examined. The results indicate that President Trump largely fulfilled almost all signs and variables of the ideal-type definition, by spreading disinformation to systematically undermine election results, interfering with and pressuring institutions, such as the DOJ, to accept conspiracy theories of election fraud, inciting large-scale protests, refusing to condemn threats against government officials and refusing to stop the attack of the Capitol on January 6, 2021. The results also indicate that democracy survived mostly because of the brave civil servants and politicians who, even under threat, secured the election result and protected the democratic institutions during the 2020 presidential election and on January 6, 2021. But even though it's been a year since Trump's attempt to overturn the election results, democracy is still under attack. Trump´s strong hold on the Republican Party has resulted in, for example, the exclusion of Republicans who stood against Trump´s attempt to overthrow American democracy and the introduction of new election laws that make it harder for people to vote.

This essay aims to analyse the motives behind President Donald Trump’s choice to remove Affirmatively Furthering Fair Housing (AFFH), a provision of the 1968 Fair Housing Act. The true motives are analysed through the lens of Rational Choice theory. The choice of theoretical framework can account as an explanation as to why the law was removed. The essay is moreover based upon drafts originating from the Department of Housing and Urban Development. The public has since the removal of the AFFH doubted the motives presented by the President, thus giving room for further scientifical exploration on the subject. The author has chosen to conduct a quantitative text analysis to present the given arguments by the administration and the Republican party and furthermore to present alternative motives. The analysis presents an argumentation analysis to further explore the strength in the arguments presented from the relevant actors. The theoretical framework provides an explanation of the choices made, namely by offering a new dimension in which to examine the true motives behind the choice to remove AFFH.

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The main purpose of this master thesis is to examine the concept of populism in the post- Gutenberg era. The research stems from a premise that the evolution of the political milieu and change of the media landscape implies a need for a different approach to analyzing populism. The decline of traditional political parties, the disappearance of political cleavages, and the personalization of politics precipitate the need to re-evaluate the debate about the right definition of populism. Based on a comparative case study of two leaders - Andrej Babiš and Donald Trump, this thesis examines how various theories of populism explain their behavior and tries to determine the most suitable option. Three definitions of populism are studied - populism as an ideology, populism as a discourse, and populism as a political style. While comparing political programs, discourse, and marketing strategies of both candidates, this thesis offers a complex insight into political campaigning on both sides of the Atlantic. At the same time, this research discusses the relationship between the concept of populism and personalized politics. These two concepts form a personalized leadership where the combination of populism and personality traits of the leader might influence the political programs, discourse, and marketing...

This dissertation consists of three essays in the field of environmental economics. The first chapter provides the first causal evidence that hostile activities online lead to physical violence. Given the recently documented relationship between pollution and social media, I exploit exogenous variation in local air quality as the first step to instrument for online aggression. In an event study setting, I find volatile organic compounds (VOCs) increase by 7% when refineries experience unexpected production outages. Together with higher air pollution, I find more aggressive behaviors both online and offline, as well as worse health outcomes near refineries. A one standard deviation increase in surrounding VOCs leads to 0.16 more hate crimes against Black people and 0.23 more hospital visits per thousand people each day. Second, I consider how emotional contagion spreads through social networks. On days with pollution spikes, surrounding areas see 30% more offensive and racist tweets and 12% more crimes; those geographically distant but socially networked regions also see offensive and racist tweets increase by 3% and more crimes by 4.5%. Nationally, overlooking spillovers would underestimate crime effects of pollution by 24%. My findings highlight the consequences of social media hostility and contribute to the public debate on cyberspace regulation. The second chapter, which is coauthored with Andrew Wilson, analyzes the relationship between weather and railway accidents. Rail thermal expansion and contraction are key considerations in rail design and construction; rail operators and rolling stock may likewise exhibit vulnerability to temperature changes. We quantify the sizes of these effects by leveraging a comprehensive dataset of railway malfunctions in the United States spanning 1997-2019. We find that both heat and cold cause elevated rates of railway malfunctions, with relatively larger increases in the number of incidents leading to a casualty as well as the number of injuries and deaths resulting from these incidents. We find that exposure to daily temperatures averaging over 30°C (86°F) leads to a 16% increase in the number of rail malfunctions, a 13% increase in the number of incidents leading to a casualty, and 18% and 36% increases injuries and deaths-effects net of any operational adjustments made to mitigate these effects. Further, while we also find that warmer locations exhibit a weaker relationship between heat and railway malfunctions, we find no evidence that companies are learning, year-over-year, how to reduce accidents. Finally, we note that effects of heat are strongest for derailments (versus other types of malfunctions) and freight trains (versus passenger trains). Our findings highlight the vulnerability of the railway system to the climate. The number of injuries and deaths associated with weather exposure-especially in comparison to operators' reported private costs of equipment failure-suggests a role for enhanced rail safety regulations and adaptation funding to protect critical heat-exposed infrastructure. The third chapter, which is a joint work with Douglas Almond and Muye Ru, explores the impact of federal policy rollback on methane leakage. Improvements in satellite measurement enable independent assessment of regulatory and climate policy. In August 2020, the Trump Administration lifted Obama-era requirements that oil and gas firms detect and repair methane leaks. We merge geo-identified data from the European TROPOMI (satellite instrument) to the specific locations of the US oil and gas infrastructure. Using a difference-in-differences design, we find a prompt increase in US methane emissions following the summer 2020 rollback. The number of high-methane emission events from the oil and gas sector more than doubled after the rollback relative to the coal sector, which did not experience the same regulatory rollback. While the oil and gas industry claims it faces a persistent, profit-making incentive to stem natural gas leaks and emissions, we find a large and nimble response by industry to changes in federal policy. Public policies that reduce methane externalities are critical given that global methane concentrations are rising at an increasing rate.

This dissertation consists of three papers at the intersection of social policy and immigration. The first paper analyzes the impact of immigrant welfare exclusion on government social spending at both an aggregate and specific social program level, using cross-national social expenditure panel data from 21 Organization for Economic Co-operation and Development (OECD) countries between 1990 and 2015 and taking advantage of the significant variation in welfare exclusivity across OECD countries by year. The second paper utilizes the variation in states’ response to the Affordable Care Act’s Medicaid expansion to investigate its effects on low-income immigrants’ inter-state mobility, specifically in-migration, and out-migration. Finally, the third paper utilizes data from the National Survey of Children’s Health to examine the effect of the announcement of the Trump administration’s revised Public Charge rule on insurance coverage and other health outcomes for children of immigrant parents.