Dr. Justin Phillips
Senior Lecturer in Political Science at the University of Waikato, New Zealand. He specializes in political communication research, particularly on social media utilizing big datasets.
Website: https://profiles.waikato.ac.nz/justin.phillips
Email: justin.phillips@waikato.ac.nz
Prof. Andrea Carson
Professor of Political Communication at La Trobe University, Australia. She researches mis- disinformation, media and political trust and election campaigns.
Website: https://scholars.latrobe.edu.au/alcarson
X / Twitter: @andrea_carson
Email: a.carson@latrobe.edu.au
U.S. Election 2024
64. Reversion to the meme: A return to grassroots content (Dr Jessica Baldwin-Philippi)
65. From platform politics to partisan platforms (Prof Philip M. Napoli, Talia Goodman)
66. The fragmented social media landscape in the 2024 U.S. election (Dr Michael A. Beam, Dr Myiah J. Hutchens, Dr Jay D. Hmielowski)
67. Outside organization advertising on Meta platforms: Coordination and duplicity (Prof Jennifer Stromer-Galley)
68. Prejudice and priming in the online political sphere (Prof Richard Perloff)
69. Perceptions of social media in the 2024 presidential election (Dr Daniel Lane, Dr Prateekshit “Kanu” Pandey)
70. Modeling public Facebook comments on the attempted assassination of President Trump (Dr Justin Phillips, Prof Andrea Carson)
71. The memes of production: Grassroots-made digital content and the presidential campaign (Dr Rosalynd Southern, Dr Caroline Leicht)
72. The gendered dynamics of presidential campaign tweets in 2024 (Prof Heather K. Evans, Dr Jennifer Hayes Clark)
73. Threads and TikTok adoption among 2024 congressional candidates in battleground states (Prof Terri L. Towner, Prof Caroline Muñoz)
74. Who would extraterrestrials side with if they were watching us on social media? (Taewoo Kang, Prof Kjerstin Thorson)
75. AI and voter suppression in the 2024 election (Prof Diana Owen)
76. News from AI: ChatGPT and political information (Dr Caroline Leicht, Dr Peter Finn, Dr Lauren C. Bell, Dr Amy Tatum)
77. Analyzing the perceived humanness of AI-generated social media content around the presidential debate (Dr Tiago Ventura, Rebecca Ansell, Dr Sejin Paik, Autumn Toney, Prof Leticia Bode, Prof Lisa Singh)
Few will forget the iconic images of former President Donald Trump emerging with a bloodied face after an assassination attempt at an election rally in Pennsylvania on July 14th 2024. It adds to the United States’ tragic, long history of assassination attempts on presidents with nearly one in 11 killed (four sitting presidents assassinated, and two surviving a shooting). As communication scholars, our interest is how modern media communicate news of these attempts (successful and otherwise), how the general public respond to this news, and what these discourses might say about the state of American politics. For example, entire volumes have documented the deeply personal impact of news of the assassination of John F. Kennedy (e.g. Russo & Moses’s Where were you? America remembers the JFK assassination) and survival of Ronald Reagan (e.g. Pillemer’s Flashbulb memories).
Thomas Matthew Crooks’ shooting of President Trump during the 2024 election campaign continues this dark history of attempts on US presidents’ lives. Nevertheless, the latest event occurs in an era where social media—instead of newspapers, radio, and television—dominate our communicative landscape. It therefore offers a unique opportunity to reveal almost real-time public responses to breaking news of an assassination attempt on a (former) President running for office.
While there will no doubt be more extensive analyses in the future, our first effort draws from a unique data source: approximately 26 thousand Facebook comments to “breaking news” of the attempt on Trump from six posts from major cable (CNN, FNC, MSNBC) and broadcast news (ABC, CBS, NBC) outlets’ Facebook public pages in the first 24 hours after Crooks pulled the trigger. The comments come from Meta’s new Content Library, which requires substantial oversight in how scholars use, analyse, and present the data.
While Meta’s conditions of use restrict exploration of individual’s comments, it approved our presentation of the following topic model (i.e. Table 1), which largely explains the thematic spread of comments responding to breaking news of the assassination attempt on Trump. For those interested in the technical details, the model was created using soft clustering of dimensionally reduced sentence embeddings from a large language model (for more see Phillips, Carson, and Jackman, 2024).
Table 1 displays the topic names (derived from statistically representative sentences and words), the “likes” each topic received (as a percentage), and the category’s relative size. We see three immediate themes emerging from the data, they are examples of: dismay; trolling, and the public’s conspiratorial thinking from both sides of the political spectrum. While some comments express dismay at the attempt, be it emotional (see Table 1 example GG), spiritual (T) or democratic (HHH), other comments are rife with attributing blame for the attack (e.g. Democrats: A), expressing conspiracy beliefs (e.g. Staged: J), and reacting with what we consider are troll-like responses. To more clearly explain the latter, see the comments of repulsion to others’ use of the laughing emoji (D) in response to the attack. As we have written elsewhere (Phillips, 2023), this RIP-trolling act wields laughing emojis as weapons to publicly attack, mock, and demean the grief of others on this platform. The six Trump assassination posts we analyzed prompted nearly nine thousand laughing emoji reactions. The unquestionably sarcastic deployment of “thoughts & prayers” (M) offers further evidence of these troll-like comments and reactions.
Conspiracy theories are also clearly present as self-contained topics in the data, ranging from characterizations of the shooting as a publicity stunt (W), and as a hoax (CCC), to criticizing Trump’s supposed fake blood (JJ) and what some sarcastically ridicule as the President’s Oscar-worthy performance (OO). However, we also note conspiracies saturate many of the other topics, for example suggesting “they” (e.g. Democrats) were unsuccessful in using the legal (II) or electoral system (VV) to defeat Trump, and so “they” have resorted to attempted murder—thereby casually inferring a conspiracy. In this way, the comments at times display an almost bipartisan belief in conspiracies, albeit different theories, used by both the politically left and right in direct response to the assassination attempt.
While there is little room to more deeply explore the data—both due to space and Meta legal constraints, there is obvious need for more detailed investigation of this kind. The comments themselves somewhat demand this, pointing to each other’s Facebook responses as further evidence of a divided nation (H) on the brink of civil war (DDD) giving us insight into the state of polarization in US politics. Our hope is that this brief contribution offers initial insights and sparks much-needed further research going forward.