Political polarization at its worst since the Civil War

Algorithms may be making political polarization worse than we think

Marc Torrens and Carlos Carrasco-Farré analyze how algorithms influence opinions and heighten our emotional responses.

It’s Not Polarization; It’s the Radicalization of the Political Right

Polarization has become the master concept for diagnosing contemporary democratic crises. The notion denotes three features: symmetry between parties, politics as an opinion space where positions diverge, and mutual repulsion between opposing camps. Yet none of these capture current realities. Across democracies, the central dynamic is not two poles drifting apart but the transformation of the political right into authoritarianism, norm breaking, and openness to political violence. Social democratic and center-right parties tend to respond in the opposite way from what “polarization” implies: by accommodating rightward. Attempts to salvage the polarization frame with modifiers (“asymmetric,” “affective,” “sectarian,” “pernicious”) concede these realities but risk hollowing out the concept’s definitional core. These limitations reveal a deeper misdiagnosis: when one party turns antidemocratic and illiberal, incivility and conflict are inevitable—but they are symptoms, not the root problem. Misdiagnosing them as the central issue leads to viewing civility and compromise as remedies, thereby risking the legitimation of authoritarian actors. This article proposes an alternative lens: the radicalization of the political right. Developed in the study of extremism, the radicalization framework better captures asymmetric change, identity-driven politics, and the mainstreaming of illiberalism. It foregrounds identity fusion, threat narratives, elite entrepreneurship, and escalation. Concepts are never politically innocent and persisting with “polarization” risks both misdiagnosing and normalizing authoritarian threats.

It’s Not Polarization; It’s the Radicalization of the Political Right

Polarization has become the master concept for diagnosing contemporary democratic crises. The notion denotes three features: symmetry between parties, politics as an opinion space where positions diverge, and mutual repulsion between opposing camps. Yet none of these capture current realities. Across democracies, the central dynamic is not two poles drifting apart but the transformation of the political right into authoritarianism, norm breaking, and openness to political violence. Social democratic and center-right parties tend to respond in the opposite way from what “polarization” implies: by accommodating rightward. Attempts to salvage the polarization frame with modifiers (“asymmetric,” “affective,” “sectarian,” “pernicious”) concede these realities but risk hollowing out the concept’s definitional core. These limitations reveal a deeper misdiagnosis: when one party turns antidemocratic and illiberal, incivility and conflict are inevitable—but they are symptoms, not the root problem. Misdiagnosing them as the central issue leads to viewing civility and compromise as remedies, thereby risking the legitimation of authoritarian actors. This article proposes an alternative lens: the radicalization of the political right. Developed in the study of extremism, the radicalization framework better captures asymmetric change, identity-driven politics, and the mainstreaming of illiberalism. It foregrounds identity fusion, threat narratives, elite entrepreneurship, and escalation. Concepts are never politically innocent and persisting with “polarization” risks both misdiagnosing and normalizing authoritarian threats.

Views of American politics, polarization and tone of political debate

In many ways, Americans’ emotions toward politics today are as negative as their evaluations of the country’s political system. Majorities say they always or often feel exhausted (65%) and angry…

New study shows just how Facebook's algorithm shapes conservative and liberal bubbles

Research conducted at the height of the 2020 election reveals new details about how Facebook's algorithms handle political content. But it suggests there are no easy fixes to political polarization.

Hyperpolitics: Extreme Politicization without Political Consequences

POLITICS AFTER THE END OF THE END OF HISTORYWhat happens when politics is everywhere, yet nothing seems to change? From the abandoned dance floors of Thatcher’s London to the mass mobilizations of Black Lives Matter, Anton Jäger traces how pub­lic life has become infused with protest, spectacle, and moral urgency — while the old infrastructure of parties, unions, and civic solidarity has been hollowed out.Hyperpolitics revisits the illusions of the “end of history” and dissects the strange energies that replaced them: viral outrage, endless culture wars, and the digital rush of causes that flare and vanish overnight. Jäger shows how the promises of post–Cold War liberalism gave way to a restless, unsteady public sphere where private pas­sions overflow into politics but rarely build enduring power.Ranging from Guy Debord and Wolfgang Tillmans to Houellebecq’s disenchanted fictions, Hyperpolitics makes sense of a world in which collective action remains fragmented and the social fabric thinner than ever. For anyone trying to grasp why our age feels so charged yet so incon­sequential, this book offers a vital map through the new contradictions of our hyperpolitical moment.

State Department Advances Trump Crackdown on ‘Far-Left Terrorism’

Critics say the Trump administration’s focus is disproportionate, as analysts raise alarms about the growing strength of far-right movements.

State Department Advances Trump Crackdown on ‘Far-Left Terrorism’

Critics say the Trump administration’s focus is disproportionate, as analysts raise alarms about the growing strength of far-right movements.

When Do Parties Lie? Misinformation and Radical-Right Populism Across 26 Countries

The spread of misinformation has emerged as a global concern. Academic attention has recently shifted to emphasize the role of political elites as drivers of misinformation. Yet, little is known of the relationship between party politics and the spread of misinformation—in part due to a dearth of cross-national empirical data needed for comparative study. This article examines which parties are more likely to spread misinformation, by drawing on a comprehensive database of 32M tweets from parliamentarians in 26 countries, spanning 6 years and several election periods. The dataset is combined with external databases such as Parlgov and V-Dem, linking the spread of misinformation to detailed information about political parties and cabinets, thus enabling a comparative politics approach to misinformation. Using multilevel analysis with random country intercepts, we find that radical-right populism is the strongest determinant for the propensity to spread misinformation. Populism, left-wing populism, and right-wing politics are not linked to the spread of misinformation. These results suggest that political misinformation should be understood as part and parcel of the current wave of radical right populism, and its opposition to liberal democratic institution.

Redesigning algorithms to intervene on social norm misperceptions during a national election

For the first time in history, civic discourse commonly occurs in digital environments in which algorithms influence exposure to social information1,2. It is increasingly important to understand whether and how these algorithms affect political discourse3–5. Here we built custom feed-ranking algorithms with full control over their features, and randomly assigned 2,000 participants to use them for 8 weeks (before and after the 2024 US presidential election). We tested whether an engagement-based algorithm (used on major social media platforms6,7) amplifies intergroup, moralized and emotional (IME) information in ways that skew perceptions of social norms around political dialogue5,8, and whether it increased engagement with IME content and perceptions of partisan animosity (compared with a reverse-chronological feed9,10). We also developed and tested a ‘diversified extremity’ algorithm to reduce the influence of extreme users11–13 to improve the accuracy of social norm perception14–16 and reduce perceptions of partisan animosity. We found that engagement-based feeds amplified IME and toxic content relative to reverse-chronological feeds, with the largest increases in moral outrage and political content. Engagement-based feeds also reduced prescriptive norm perception accuracy (albeit in an unexpected direction) and increased perceived partisan animosity. However, they did not significantly alter users’ own engagement behaviours. The diversified extremity algorithm reduced IME and toxic content exposure, improved prescriptive norm accuracy, yet maintained comparable platform enjoyment—suggesting that reducing the influence of extreme users can curb algorithmic distortions without diminishing user experience.

The political effects of X’s feed algorithm

Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects1. Here we present results from a 2023 field experiment on Elon Musk’s platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects. Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users’ feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X’s algorithm has persistent effects on users’ current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship.

The political effects of X’s feed algorithm

Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects1. Here we present results from a 2023 field experiment on Elon Musk’s platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects. Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users’ feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X’s algorithm has persistent effects on users’ current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship.