Balancing Platforms: How U.S. Senate Candidates Campaign Across Twitter, Facebook, and Instagram

The aim of this study is to identify and compare the patterns of United States Senate candidates’ campaigns on Facebook, Twitter, and Instagram during the 2022 United States Senate Midterm election. While research on political messaging on social media is vast, most of it is confined to a single platform, usually Twitter, and uses programming languages to code social media posts. This work is designed to fill these gaps in the literature by manually performing a cross-platform analysis. I do this by coding a post’s tone and content as it is related to policy issues and other non-policy related topics. Using my own data, my findings support that Senate candidates use different campaign strategies across social media platforms. Specifically, I find that on Twitter, candidates relay more information about themselves and their opponent while using Instagram to serve other campaign functions. I also find that candidates discuss more policy issues on Twitter and discuss these issues to a greater extent when compared to Instagram and Facebook. In addition, I find that in general candidates post a substantial number of non-political posts showcase themselves in their community across all platforms.Bachelor of Art

Produksi Hate Speech dalam media sosial: Kasus Hate Speech Terhadap Joko Widodo Menjelang Pemilu 2019

Dewasa ini media sosial telah banyak berpengaruh terhadap masyarakat Indonesia, bahkan hampir seluruh masyarakat Indonesia memiliki media sosial. Banyaknya pengguna media sosial di Indonesia tidak hanya memiliki dampak positif bagi pengguna akan tetapi juga memiliki dampak negatif, salah satu dampak negatif dari pesatnya perkembangan media sosial adalah adanya ujaran kebencian terhadap seseorang atau kelompok tertentu yang dilakukan di media sosial. Penelitian ini membahas tentang Hate Speech dalam media sosial dengan studi kasus pengaruh ujaran kebencian terhadap Joko Widodo. Penelitian ini menggunakan pendekatan kualitatif yang ditujukan untuk mengeksplorasi dan mendapatkan pemahaman yang mendalam tentang efek dan pola dari ujaran kebencian dalam kasus ini. Dari hasil penelitian ini ditemukan bahwa ujaran kebencian yang dilakukan di media sosial Facebook dan Instagram memiliki pola pembuatan dan penyebaran ujaran kebencian yang jelas. Sedangkan dipihak Joko Widodo, ujaran kebencian yang terjadi terhadap Joko Widodo untuk saat ini tidak banyak berpengaruh terhadap elektabilitas Joko Widodo menjelang pemilu 2019 akan tetapi jika ujaran kebencian tersebut dibiarkan maka akan memiliki potensi untuk menurunkan elektabilitas Joko Widodo. Mengatasi hal tersebut penanganan dari komunitas politik disekitar Joko Widodo sangat dibutuhkan demi menjaga elektabilitas Joko Widodo menjelang pemilu 2019

Social Media, Money, and Politics: Campaign Finance in the 2016 US Congressional Cycle

With social media penetration deepening among both citizens and political figures, there is a pressing need to understand whether and how political use of major platforms is electorally influential. Particularly, the literature focused on campaign usage is thin and often describe the engagement strategies of politicians or attempt to quantify the impact of social media engagement on political learning, participation, or voting. Few have considered implications for campaign fundraising despite its recognized importance in American politics. This paper is the first to quantify a financial payoff for social media campaigning. Drawing on candidate-level data from Facebook and Twitter, Google Trends, Wikipedia page views, and Federal Election Commission (FEC) donation records, we analyze the relationship between the topic and volume of social media content and campaign funds received by all 108 candidates in the 2016 US Senate general elections. By applying an unsupervised learning approach to identify themes in candidate content across the platforms, we find that more frequent posting overall and of issue-related content are associated with higher donation income when controlling for incumbency, state population, and information-seeking about a candidate, though campaigning-related content has a stronger effect than the latter when the number rather than value of donations is considered.Comment: Under review. Main article + Supplementary Informatio

Incivility in 2022 Senatorial Elections

This honors capstone project will examine the effect of social media, specifically Twitter, on U.S. senate elections in 2022. It will track the tweets of personal and official campaign Twitter accounts from the end of the primary until election night in two “Toss Up” or highly contested seats in the 2022 senate elections. This project will examine the winner of the Republican and Democrat primaries only. All the tweets from the timeframe will be tracked and categorized by intention or use of the tweet. These categories will break down the tweet into what it was meant to do be it campaigning, informing, or messaging. The research will break the tweets down by type and compare it to the trends seen in traditional media such as print, signage, radio, television, and any website use. The conclusion will look to show the similarities and differences in style of the candidates and the other forms of campaigning

Meet your audience where they are: The dissemination and reception of political messaging among young voters [Paper]

In an ever-changing media environment and growing influence of young voters, creating and disseminating messages that will reach this intended audience is a complicated and difficult task for political campaigns. Social and new media changes with each election cycle, so following standards of the most previous campaign is following an outdated strategy which may not break through in the newest media environment. With an increasing interest in strategies to reach young voters in the electorate, political campaigns and their candidates are disseminating messages online and on social media, where an increasingly large number of the voting bloc is getting their information. In the sea of available information online, the effectiveness of breaking through and being seen by voters is increasingly difficult. Unpredictable viral moments and negative perceptions of paid content online adds incredibly complicated elements into the mission of successfully reaching and resonating with the intended audience of voters. As such, this study reflects on the success and failures of campaigns within the 2020 Democratic Primary to disseminate messages to an audience, particularly college-aged voters, and how these successes and failures establish a basis for developing strategy and messaging for future political campaigns

Political Platforms: Technology, User Affordances, and Campaign Communications

Political candidates communicate across a wide number of platforms during their campaigns, including television, Facebook, Twitter, debates, radio, and newspapers. However, these platforms are not the same. Each is made up of a number of different technical features and user affordances. Technical features shape the type of content that can be transmitted through each platform and user affordances describe how platforms are interpreted and used by candidates. The interaction between features and affordances suggests that content ought to vary across platforms, even when the user of those platforms is the same. I argue in this project that the interaction of features and affordances inclines platforms towards certain ideological audiences and allows for interactions between candidates. I term these the audience and channel of the platform. Audience can range from narrow to broad indicating the degree to which the audience is ideologically homogenous. Channel goes from shared to independent as an indication of how easily candidates can directly interact with their opponents. I find that broad audience platforms with independent channels are, on average, more negative than narrow audience, shared channel platforms. I also find that policy content is more present in broad audience platforms. Finally, I find that visual communications also exhibit similar patterns. Broad audience and independent channel platforms are markedly more negative and contain more policy language than narrow audience and shared channel platforms. These findings stand up with multiple test of robustness, including different dictionary specifications, word counts, and different elections. These findings suggest that audiences are being exposed to systematically different content, depending on where they get their information from. This could have meaningful and serious implications for our understanding of political knowledge, polarization, candidate evaluations, and voting. I offer the Platform Audience and Channel Theory as a tool for researchers to study current platforms and a way to understand platforms that have not yet been developed.PHDCommunicationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163218/1/dhrice_1.pd

Exploring Thematic Diversity In News Coverage And Social Media Activity Of Political Candidates Using Unsupervised Machine Learning

The relationship between media and politics has been at the core of communication research for over a century. Previous research has examined the impact of both volume and tone of news coverage of political candidates on their electoral success, and the relationship between the volume of candidates’ social media activity (though not its tone) and electoral success. While past research found a positive relationship between these features and electoral success, recent criticisms have called into question the independent nature of these media factors. Moreover, while past research has paid some attention to volume and tone, researchers have yet to examine other key features of discourse represented in candidates’ coverage as a whole. One such feature is the extent to which a political discourse is unidimensional or multidimensional in nature, referred to in this study as thematic diversity. This is due, in part at least, to the complex nature of thematic diversity making its estimation challenging. Analyzing over 120,000 Tweets written by 142 U.S. Senate candidates during the 2012-2016 election cycles, as well as over 420,000 news articles covering 330 U.S. Senate candidates during the 2008-2016 election cycles, this study systematically explores the relationship between electoral success of political candidates and the volume and tone of their news coverage and social media activity. Using a wide array of controls, this study explores the independent (or dependent) nature of these media features. More importantly, this study goes beyond these previously studied media features, to systematically and empirically explore the relationship between thematic diversity in both candidates’ news coverage and social media activity, and their electoral success. Drawing on the conceptualization of diversity in various fields from biology, to physics and information sciences, and using two unsupervised machine learning methods, semantic network analysis and topic modeling, this study offers a novel approach to the conceptualization and estimation of thematic diversity, accounting for the variety, balance and disparity of various themes in a given corpus. Using these methods, this study offers evidence for a significant, negative, and semi-independent relationship between thematic diversity and electoral success, in both news media and social media