Prof. Heather K. Evans
John Morton Beaty Professor of Politics at the University of Virginia’s College at Wise. Her research interests are congressional elections and political communication. She is the author of Competitive Elections and Democracy in America: The Good, the Bad, and the Ugly.
Twitter: @HeatherKEvans
Email: heatherkevans@uvawise.edu
Dr. Jennifer Hayes Clark
Associate professor of political science at the University of Houston. Her areas of specialization include legislative institutions, state politics and public policy. She is the author of Minority Parties in U.S. Legislatures: Conditions of Influence.
Email: jclar2@central.uh.edu
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)
During the 2024 U.S. presidential election, it was impossible to escape conversations surrounding gender and its potential impact in the race. Not only did we have a second woman running against Donald Trump for the presidency, but in the summer of 2022, Roe v Wade was overturned by the Supreme Court and was key in mobilization and turnout efforts in the previous midterm election. Heading into Election Day 2024, while the economy and concerns about democracy rang out as the most important issues identified by the American public, voters—especially self-identified Democrats—also mentioned issues like education, healthcare, and abortion (all defined as so-called “women’s issues”). Gender was also identified by pollsters as having a large impact on understanding voter decision making, with predictions that this particular race would result in the largest “gender gap” in our history, with women picking Vice President Kamala Harris and men picking former President Donald Trump by as much as a 51-point gap especially among men and women under 30 (CNN – NYT/Sienna College Poll).
Given our previous published research on the impact of gender on the campaigning styles of female candidates for Congress, and regarding how Trump and Clinton campaigned in 2016, we would like to share how gender played a role in this presidential election on Twitter/X. Our previous research highlights three key findings:
- Women candidates send more tweets than men. From 2012 to 2022, women running for seats in the U.S. Congress have consistently sent more tweets on average than male candidates. During the presidential election of 2016, Clinton also sent significantly more tweets than Donald Trump.
- Women candidates are more likely to attack their opponents. In our previous work, we have shown that female congressional candidates are also consistently more likely to “go negative” about their opponents. The same was true for the last presidential election with a female candidate. While proportionately, both Clinton and Trump spent the same amount of total tweet time focused on negativity, Clinton had almost twice the number of tweets attacking Trump as he did attacking her (he had a decent number of tweets focused on attacking other individuals and institutions, like the government or media).
- Female candidates are more likely to discuss “women’s issues.” Our research shows that women are more likely to talk about all issues on Twitter, especially the so-called “women’s issues.” Clinton also was significantly more likely to discuss “women’s issues” in 2016, sending triple the number of tweets as Trump did on these topics.
To examine whether these findings hold in 2024, we collected tweets sent by Harris and Trump from September 1 to November 4th. It is important to note that Twitter/X as a platform has changed considerably since the 2022 Midterms. Elon Musk bought the platform in October of 2022, and many political candidates have either stopped using the social networking site or are using it less often. Trump was also banned from the platform after January 6th, 2021, and was then allowed to re-join the platform by Musk in November 2022 (directly after the purchase of the site). He did not use the platform again until he posted his mugshot in August of 2023.
Consistent with our previous findings, Harris tweeted over four times as often as Trump from the beginning of September to Election Day (986 tweets to 245). We coded each candidate’s tweets to determine whether they attacked their opponent. Our second major finding also holds. Harris sent 301 tweets (30.53%) criticizing Trump, while Trump sent 60 tweets (24.49%) criticizing Harris.
When we examine the tweets further in terms of their policy content, we find that Trump only sent a total of 12 tweets, or 4.90% of total tweets, about “women’s issues,” while Harris sent 222 tweets, or 22.52% of her total tweets, discussing these topics. As Figure 1 shows, Harris sent more tweets across all issues affecting women as a group, with the highest numbers being about family (77 tweets) and women (67 tweets). By contrast, Trump only sent 10% as many tweets about family (7 tweets total), which was the highest number of tweets he sent that referenced any of these topics, most of which had 0 tweets. The framing of these issues also differed for Harris and Trump. Trump’s tweets about women or girls tended to focus on young girls, like Mimi Ramirez Rodriguez, being kidnapped and murdered by an illegal alien; while Harris’s tweets about women or girls tended to focus on stories about how abortion bans have affected women or supporting women’s reproductive freedom. Trump’s tweets about families focused on how Harris’s economic policies would harm average American families, while Harris’s tweets about families focused on how Trump’s policies would harm middle class families, her policies would lift up middle class families, and how Trump’s policies would prevent families having access to IVF.
Our analysis of these campaign tweets confirms our previous findings. Harris used Twitter/X very similarly to Clinton, both in terms of the number of posts, tone, and content, while Trump rarely discussed “women’s issues.” Ultimately, Clinton and Harris’s concerted appeals to women voters were not enough to garner the support needed to win the election.