![]() ![]() ![]() The increase is particularly noticeable after late June and July, when Fetterman ramped up his inflammatory content towards Oz. Looking at the plots, we see an increase in the number of keywords and the number of replies over time for both of the candidates. These plots are populated with “Xs,” which show the number of replies to a given tweet, and gold dots, which show the number of keywords which appear in the replies to that tweet. To begin our analysis, we’ll first look at two plots, which show the incidence of all of these keywords from January to September 2022 for both candidates. (For those interested in the full list of keywords, I’ve included it at the end of this post.) Additionally, I tracked the words “health” and “stroke,” since Oz has made a particular point of claiming that Fetterman’s stroke contributes to his unfitness to serve. The Fetterman-related words I tracked include “crime,” since Oz has frequently criticized his policies as being “lenient on crime,” and the topic has become central to the campaign as a key issue. I also tracked the word “crudité” over time since Fetterman highlighted an awkward video of Oz at the grocery store, where Oz laments Biden-driven inflation by demonstrating how expensive the purchase of ingredients for a crudité can be Fetterman’s tweet sparked national laughter and Pennsylvanian indignation about Oz’s stunt. The words associated with Oz, for example, include, “new jersey” or “nj” since Fetterman has repeatedly mocked Oz’s questionable Pennsylvania residency. Finally, I estimated the ideologies of the users who replied to the tweets to understand whether more negativity was coming from liberal or from conservative users, and whether that differed for Oz’s and Fetterman’s Twitter accounts.Īfter combing through tweets and articles from the past ten months, I generated a list of “Oz-specific” and “Fetterman-specific” keywords, as well as words that I concluded were central to the campaign as a whole, such as “abortion” and “inflation.” I counted up the number of times these words appeared in the replies to the tweets for the respective candidate to gauge how the conversation evolved over time.Next, I analyzed the sentiment of replies to these tweets to gauge how negative or positive they have become over time.Second, I quantified the use of keywords, or words I found were relevant to the campaign, in the replies to the tweets generated by these candidates.Oz from January to September 2022 using the Twitter API. First, I scraped all of the tweets and replies to the tweets posted by John Fetterman and Dr.In conducting this analysis, I hoped to understand the role that tweets– and more specifically, memes– can hold in a race that has been so close and could become consequential beyond Pennsylvania’s borders. I decided to apply these tools to this Senate race, where Twitter and meme-making has taken center stage, by quantifying and understanding the patterns in these candidate’s tweets. Here at the MIT Election Data and Science Lab, we have developed tools to analyze and scrutinize trends on social media, particularly on Twitter. Oz responded with equally aggressive online fervor. In his physical absence, he migrated much of his campaign activity to Twitter, and for months he posted memes highlighting and mocking the shortcomings of his Republican opponent, the former TV personality and cardiologist Dr. After suffering a stroke just days before the Pennsylvania primary election, current lieutenant governor and Democratic candidate John Fetterman took a break from the campaign trail to recover. ![]()
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