| Naslov: | Evaluating depolarization-oriented news ranking strategies using LLM-generated articles |
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| Avtorji: | ID Sergaš, Uroš (Avtor)
ID Tkalčič, Marko (Avtor)
ID Ferwerda, Bruce (Avtor) |
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| Datoteke: |  RAZ_Sergas_Uros_2026.pdf (1,09 MB)
MD5: 3BECEB61C082BB3F97C8A90EA6D511B2
RAZ_Sergas_Uros_2026.pdf (1,09 MB)
MD5: 3BECEB61C082BB3F97C8A90EA6D511B2
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| Jezik: | Angleški jezik |
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| Vrsta gradiva: | Neznano |
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| Tipologija: | 1.08 - Objavljeni znanstveni prispevek na konferenci |
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| Organizacija: | FAMNIT - Fakulteta za matematiko, naravoslovje in informacijske tehnologije
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| Opis: | Algorithmic news ranking and large language models (LLMs) increasingly mediate how citizens receive political information. While personalization is often criticized for reinforcing echo chambers, ranking has also been proposed as a lever for depolarization by shaping exposure to cross-cutting viewpoints. We test this claim in an online experiment (N=100, Prolific) using five LLM-generated news articles on gun legislation spanning pro–gun freedom to pro–gun control. All participants read the same articles; the only manipulation was article order, instantiated as a random baseline and six stance-aware depolarization-oriented strategies (counter-narrative sandwich, balanced alternation, and directional gradients). Pre–post questionnaires measured ideological self- placement (feeling thermometer) and affective evaluations of gun-control and gun-freedom advocates. Across six research questions, we find no statistically reliable evidence that any ranking strategy reduces ideological or affective polarization relative to the baseline, nor that stance-conditioned assignment improves outcomes. These results suggest that, under the constraints of a short, single-session, single-topic exposure study with LLM-generated article stimuli, article ordering alone did not produce detectable depolarization effects. The findings motivate future work to design longer-term, multi-topic, and more interactive solutions for mitigating affective polarization. |
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| Ključne besede: | news recommendation, political polarization, affective polarization, ranking strategies, large language models |
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| Verzija publikacije: | Objavljena publikacija |
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| Leto izida: | 2026 |
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| Št. strani: | Str. 118-126 |
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| PID: | 20.500.12556/RUP-23090  |
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| UDK: | 004.8 |
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| ISSN pri članku: | 1613-0073 |
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| COBISS.SI-ID: | 280133891 |
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| Datum objave v RUP: | 02.06.2026 |
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| Število ogledov: | 135 |
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| Število prenosov: | 6 |
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| Metapodatki: |    |
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