Political Polarization & Partisan Dynamics
Framing the field: fragmentation, bias, and the evidence-recommendation gap
Two meta-level papers bookend this collection by interrogating the field itself. Falkenberg2026-ka diagnoses political polarization research as disciplinarily fragmented and geographically skewed toward the US, calling for integrated, globally equitable frameworks — a call this very topic answers by spanning Italian, Brazilian, Scandinavian, and pan-European cases alongside the usual American ones. van-Eck2026-xg complements this with a sobering systematic review: depolarization recommendations in the literature are rarely grounded in the depolarization evidence scholars themselves produce, resting instead on unexamined normative commitments to deliberative democracy. Together they set a methodological conscience for the rest of the corpus — a reminder to distinguish what is empirically shown from what is merely hoped for, and to resist treating the US case as the default.
The Brazilian axis: Bolsonarismo, misinformation, and eroded trust
Brazil emerges as the richest single national case in this set, anchored by a cluster of papers tracing how Bolsonaro-era disinformation degraded democratic trust and intensified intolerance. Rossini2026-jn and Rossini2026-mj use companion panel surveys around the 2022 election to show that belief in electoral fraud misinformation predicts both lower political tolerance and lower trust in results, while mainstream news use — even among Bolsonaro voters — bolsters electoral trust, positioning journalism as a source of resilience against elite-driven disinformation. Kansaon2025-id documents the WhatsApp infrastructure behind this dynamic, finding coordinated inauthentic networks that translated online misinformation into real-world mobilization, including the doxxing of Supreme Court justices and the January 8 coup attempt. Ventura2025-sw extends this messaging-app focus experimentally, showing WhatsApp’s distinct informational role compared to feed-based platforms. Marino2026-he then offers a longitudinal corrective to static echo-chamber assumptions: within a pro-Bolsonaro Facebook network, affective engagement proved highly unstable, with a marked 2023 inflection around Lula’s inauguration and the coup attempt bringing declining emotional intensity and rising internal debate — suggesting hyperpartisan communities are porous and event-driven rather than sealed. Rodarte2026-dk examines elite-level narrative contests during the Manaus healthcare collapse, showing how pro- and anti-Bolsonaro parliamentarians pursued rival forms of epistemic authority. Ventura2026-yc closes the arc with the 2024 X ban, revealing a durable “sorting ratchet”: conservative users disproportionately circumvented the ban while liberals went silent, permanently shifting the platform’s political center of gravity rightward. Inacio-da-Silva2026-zf rounds out the Brazilian material with an earlier auditing effort on irregular Facebook political ads in the 2018 election, prefiguring later platform-accountability concerns.
Italian and Scandinavian comparative cases
Giglietto2019-882f1900 provides the Italian anchor, examining the 2018 election to show that populist-aligned news sources (Five Star Movement, League) are more “insular” on Twitter, and that M5S uniquely mastered a sharing/commenting logic that amplified favorable coverage while contesting unfavorable coverage — evidence that populist digital success rests on strategic exploitation of hybrid media ecologies rather than simple self-segregation. Scandinavian evidence complicates any assumption that multiparty, less-polarized systems escape these dynamics: Kalsnes2025-zb finds that populist parties across Norway, Sweden, and Denmark are especially adept at eliciting “Angry” Facebook reactions, which mobilize shares more than “Love” does, while Larsson2026-ro traces a decade of Norway’s Progress Party leadership, showing that negative sentiment has risen over time and reliably drives shares and comments even as likes track positive content — together suggesting a two-tier engagement logic (negativity for virality, positivity for lightweight affirmation) that recurs across otherwise calm party systems.
Radical-right amplification and elite misinformation strategy
A strong thread ties misinformation to elite political strategy rather than generic platform pathology. Tornberg2025-ir shows across 26 countries that neither populism nor right-wing ideology alone predicts elite misinformation sharing — their combination, radical-right populism, does, tying the phenomenon to a legitimacy crisis of liberal institutions rather than a diffuse “post-truth” condition. Knupfer2025-vt traces a parallel mechanism inside the US Republican Party: a “logic of connective faction” whereby ideologically extreme members build ties to hyper-partisan digital surrogates, using the sudden rise of “Critical Race Theory” as a diagnostic case. Bennett2025-xs generalizes this into a full theoretical intervention, arguing that “technocentric” (disinformation/algorithm) and “institutionalist” (party/elite) explanations of democratic backsliding must be integrated via a “communication-as-organization” framework in which digital surrogate organizations pull conservative parties toward illiberalism — with comparative nods to AfD, Orbán, and EU radical-right campaigns. Iris2026-pg supplies cross-national media evidence for this normalization dynamic, finding disproportionate news visibility for Radical Right actors across the 2024 European Parliament elections regardless of electoral strength, intensifying in the campaign’s final weeks. Gattermann2025-yx adds a citizen-level companion, linking far-right electoral performance to elevated public disinformation concern. Yoo2026-ev examines the discursive machinery underneath: both left- and right-wing hyperpartisan US outlets weaponize the term “fake news” to redraw Hallin’s spheres of legitimacy and deviance rather than to describe actual fabrication.
Platform architecture, algorithms, and moderation design
A distinct cluster probes how platform mechanics — feeds, ad delivery, and crowdsourced moderation — causally shape partisan exposure. Gauthier2026-iq’s field experiment on X’s algorithmic feed finds real, asymmetric, and persistent conservative attitude shifts (via induced following of activist accounts) that a comparably designed 2020 Meta/Facebook study on ad removal (Allcott2025-jb) did not detect for political ads — the difference illuminating how organic feed-ranking versus paid advertising interventions can yield divergent findings about platform effects. Giglietto2026-632ef967 extends this into the temporal dimension: sharing-to-viewership amplification on Facebook fluctuates with governance interventions like the 2020 “break the glass” measures, showing Facebook as an active curator whose partisan penalties and quality rewards shift with political crisis rather than being fixed structural features — a claim that complicates the earlier, more static picture in Bakshy2015-rn, the classic finding that individual click choices suppress cross-cutting exposure more than Facebook’s algorithm does. Brady2026-ln’s Bluesky field experiment operationalizes an alternative design logic directly: engagement-based feeds amplify intergroup/moralized/emotional content and distort social-norm perceptions, while a “diversified extremity” algorithm curbs this without sacrificing platform enjoyment — offering one of the few prescriptive, empirically grounded design interventions in the set. On moderation specifically, Renault2025-uh and Bouchaud2026-np both scrutinize X’s Community Notes: the former shows Republicans are flagged 2.3x more often than Democrats even under a crowdsourced, cross-partisan-agreement system (undercutting claims of fact-checker bias), while the latter argues the bridging design structurally undermoderates polarizing content by construction, with electoral-integrity risks as Community Notes is exported globally. Votta2025-xz and Kim2026-wg extend the platform-mechanics lens to advertising: ad delivery algorithms shape reach and cost opaquely, and Russia-linked 2016 voter-suppression ads were geo-racially targeted with measurable turnout effects once heterogeneous (rather than average) treatment effects are examined.
Measurement, method, and the ideology of news sharing
Several papers focus on how partisanship and polarization are measured, cautioning against naïve operationalizations. Eady2025-vm introduces a unified ideology-scaling model from URL-sharing behavior spanning media, politicians, and the public, finding that ideologically extreme legislators dominate volume and extremity of shared news, linked to electoral safety. Green2025-ap shows that domain-level partisanship scores mask enormous story-level heterogeneity, especially for “moderate” sources — a “curation bubble” argument that reframes apparent polarization as networked identity performance rather than pure informational segregation. Gaisbauer2025-by and Mosleh2024-op both critique the field’s overreliance on outlet-level, single-platform (typically Twitter) measures, calling for multi-level and cross-platform approaches; Lai2024-to extends latent ideology estimation to YouTube videos via Reddit sharing patterns. Schemer2026-mh’s specification-curve analysis delivers a cautionary punchline for this whole methods thread: across 504 measurement combinations, partisan-media-polarization relationships vary enormously in magnitude depending on how slant and polarization are operationalized, though never in direction — meaning much of the field’s apparent disagreement may be a methodological artifact. Sarmiento2025-as proposes an unsupervised framing-analysis pipeline as a further methodological contribution to surfacing latent polarization structure. Ghezzi2023-8bebc91f shows a related dynamic in science journalism: UK newspapers’ political orientation predicts which COVID-19 scientists (Great Barrington vs. John Snow signatories) they cite, with segregation extending into academic co-authorship and Twitter sharing.
Narrative, emotion, and the cultural life of disinformation
Running counter to fact-centric paradigms, a cluster reconceives disinformation and polarization as narrative and affective phenomena. Marwick2026-qd argues disinformation functions as cross-platform, identity-affirming, cathartic story rather than discrete false claims, explaining why domain-based detection fails. Elfes2026-jb operationalizes this narratologically via Greimas’ actantial model on Israeli-Palestinian YouTube discourse, finding that polarization lives more in video narratives than in the comments beneath them. Starbird2025-jj’s evidence-frame framework similarly shows Arizona election-integrity rumors arising from frames imposed on largely accurate evidence via quote-tweet “call and response” dynamics. Grusauskaite2026-po extends this interactionist lens to “Great Reset” conspiracy discourse, arguing collective identity and symbolic boundary work — reclaiming “conspiracy theorist” as a badge of honor — sustain these communities more than ideological content or platform affordances. Anwar2024-34dba628’s review of Facebook Reactions research corroborates the emotional-engagement logic threading through Kalsnes and Larsson above: anger reliably drives engagement with political content. Van_Erkel2026-mk identifies a novel bias in this affective landscape, the “hostile misinformation effect,” whereby partisans believe their own side is disproportionately targeted by misinformation — amplified by interest, identity strength, and (unexpectedly) electoral winner status. Karlsnson2026-hd shows a related asymmetry: media narratives about election interference heighten perceived division and affective polarization specifically when the opposing party is portrayed as beneficiary, even though aggregate exposure has no effect — reinforcing that discourse about disinformation can itself be a polarizing vector independent of the interference’s actual success. Lieu2025-nl extends the content-versus-form question to climate misinformation, finding that argument content (attacking climate solutions) matters far more for perceived veracity and polarization than logical fallacy type.
Alternative media ecosystems and cross-national structure
Zhu2026-tn and Dehghan2026-sy both examine structural fragmentation from a network perspective — the former showing that alternative/mainstream media audience overlap in Europe depends on media-system type and populist parties’ institutional access, the latter showing minimal cross-ideological overlap even among discursively similar political subreddits, challenging the idea that spaces like r/politics function as a Habermasian town square. Kristensen2025-ni poses the alternative-platform question directly, asking whether platforms like Gab or Truth Social independently drive discursive polarization, a question Bennett2025-xs and Knupfer2025-vt answer institutionally by showing such platforms function as digital surrogate organizations feeding elite radicalization.
Emerging directions: LLMs and normative responses
Two final papers point toward where the field is heading methodologically and normatively. Lee2026-je shows that LLMs can infer political alignment from ostensibly nonpolitical text with troubling accuracy, raising privacy and micro-targeting concerns that echo the ad-targeting worries in Kim2026-wg and Votta2025-xz. On the normative side, Esau2025-tf proposes “deliberative reciprocity” and “inclusive listening” as theoretical antidotes to destructive polarization, directly answering the evidentiary gap that van-Eck2026-xg identifies — a fitting close to a literature that, across Brazilian coup attempts, Italian populist insularity, Scandinavian anger, and algorithmic amplification alike, keeps returning to the same unresolved question: how much of what looks like polarization is platform design, how much is elite strategy, and how much is the enduring human appetite for stories that confirm who we already are.