How has perceived media bias in the US changed since 2020 and during the 2024 election cycle?
Executive summary
Perceived media bias in the United States intensified after 2020 and crystallized into sharper partisan narratives during the 2024 election cycle, driven by heightened public distrust, algorithmic amplification of partisan content, and organized disinformation campaigns [1] [2] [3]. Independent rating projects and watchdogs expanded and updated their bias maps ahead of 2024 even as polls and research showed the public remained divided over whether coverage favored one candidate or another [4] [5] [6].
1. The baseline shift since 2020: distrust and appetite for “unbiased” sources
After 2020 Americans reported unusually high searches for unbiased news and rising skepticism about mainstream outlets, with a Gallup/Knight finding that roughly half of Americans believed many national news organizations intended to mislead or persuade rather than inform, a climate that set the stage for intensified perceptions of bias in subsequent cycles [1].
2. Structural responses: more measurement, more maps
Media-rating organizations expanded their tools and audiences between 2020 and 2024—Ad Fontes and AllSides substantially grew their charts and databases, updating flagship media bias charts semiannually or ahead of the election to cover thousands of sources and to re-evaluate outlet placements as public attention peaked [4] [5]. These projects emphasize multipartisan methodology but are themselves contested: Ad Fontes’ approach uses cross-spectrum analysts and has been both praised for rigor and criticized as imperfect by observers across the political aisle [7] [8].
3. The 2024 cycle’s accelerants: disinformation, AI, and social algorithms
The 2024 campaign was characterized by organized disinformation efforts amplified on social platforms and sometimes recycled into mainstream coverage; Brookings documents how coordinated campaigns and meme-driven narratives shaped public attention, while research on platform algorithms and Twitter/X shows measurable amplification patterns that influenced what users encountered during the critical run-up to the election [2] [3]. Independent watchdogs and platforms’ policy choices—strained by political pressure and high-profile controversies over moderation—added to perceptions that platforms, and by extension the media ecosystem, were acting with partisan effect [9].
4. What the public actually said in 2024: mixed evaluations and partisan lenses
Surveys captured a complicated picture: a Pew finding reported a majority (58%) saying the media covered the 2024 election at least somewhat well even as substantial minorities judged coverage poorly, and partisan splits persisted in how easily people found reliable information and whether they trusted mainstream coverage [6]. Polls and tracking studies also recorded asymmetric perceptions about which candidate benefited from coverage—one October 2024 snapshot found a larger share saying coverage favored Kamala Harris than said it favored Donald Trump, illustrating how perceived bias is often shaped by who a respondent dislikes or supports [10].
5. Narrative fights over responsibility and effect
Scholars and opinion writers debated whether mainstream outlets failed substantive coverage (for example on candidate fitness and health), whether liberal bias blinded reporters to risks, or whether anti-Trump scrutiny amounted to institutional weaponization that backfired politically; Columbia and AEI pieces exemplify these competing critiques, with some arguing media laxity or bias cost Democrats and others arguing journalists were doing overdue scrutiny [11] [12]. Meanwhile industry analyses tracked media “share of voice” and topic shifts—showing both outlets’ thematic choices (immigration vs. interviews) and how coverage emphases differed across the spectrum—confirming that coverage selection, not just accuracy, shapes perceptions [13] [14].
6. Bottom line, caveats and open questions
Perceptions of media bias since 2020 increased in intensity and became more polarized during the 2024 cycle because of a confluence of public distrust, expanded measurement tools that made bias more visible, algorithmic amplification, and coordinated disinformation; however, majorities in some surveys still judged coverage as adequate, and many disputes are about emphasis and narrative framing rather than baseline factuality [1] [4] [2] [6]. This assessment is constrained to the reporting and studies summarized here; comprehensive causal claims about how bias perceptions changed at the individual level would require longitudinal experimental data beyond the sources provided [7] [3].