Discussion around the nature of political content on X poses significant implications for the future of the way political campaigns should target interventions on social media. Highly targeted hashtags are seen to be more engaged with on X, and so “attack” hashtags or hashtag hijacking may be useful interventions for a campaign to take. The timeframe a campaign chooses to intervene on social media is significant as well, content grows increasingly polarized as the election day itself looms closer. Disseminating information that is neutral or gathers positive sentiment from users may be useful in this time frame.
But as Corsi’s findings have shown, positive and neutral content elicits engagement on X far less readily than negative or “toxic content,” does. Moreover, right-leaning tweets experience preferential bias as well as higher engagement outcomes, the accounts associated with the top tweet from each dataset were all created by a right-leaning user or politician. If, “high toxicity tweets and those with right-leaning bias see heightened amplification,” (Corsi 13) and X ai information is trained on the most amplified tweets, then interventions from democratic campaigns may be futile.
This data provides insights into political interactions on X, what CNN (a left-leaning media outlet) has called “a far right echochamber.” While true information can certainly be disseminated with and interacted with on X, the data suggests that it will likely be drowned out the the amplification effects of the most “toxic” tweets.
Ultimately, “sounds like she’s voting for Trump,” the most liked tweet amongst all three time frames of data, rang true. As the most popular tweets in the election day dataset postulate, Harris lost in key swing states, and Trump won the election. Because the data from PEW and AP Votecast demonstrate that not every Harris and Trump voter actively uses X, further research should examine the use of hashtags for engagement amplification across Tiktok, Instagram, and other social media platforms, attempting to detect political bias and understand what the most impactful engagement strategies are. Her clear loss on X may not be the reason that Harris lost the 2024 election, but it provides clear insights into the type of content that influenced voters who frequently use the platform, and the ideas that were most circulating among Americans up until election day.
Even the brash nature of the Brat campaign was not loud enough to dominate the conversation around the US election on X. This research reveals that maybe the solution for democratic campaigns is to be even louder, or maybe not even celebrity partnerships, bold and lime green font, and brazen hashtags can be heard amongst a platform that uses machine learning in the form of both algorithmically and and AI generated content to boost the most “toxic” tweets.