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Bengali headlines show frequent negative emotional framing, study finds

By PulseAugur Editorial · [1 sources] ·

Researchers have analyzed Bengali news headlines to understand the emotional tone and affective framing used in low-resource media. Using the Gemma 3-4B model for zero-shot inference, they processed 300,000 headlines and found a prevalence of negative emotions such as anger, sadness, disappointment, and fear. A small validation study indicated the model's estimates are useful, though not a definitive benchmark. The study proposes a bias-sensitive news interface to help readers identify emotional framing patterns across different news sources. AI

IMPACT Highlights potential for LLMs to analyze media bias and inform user interfaces for news consumption.

RANK_REASON The cluster is about an academic paper detailing a computational analysis of media bias using an LLM. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Bengali headlines show frequent negative emotional framing, study finds

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The cluster is about an academic paper detailing a computational analysis of media bias using an LLM. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Mohd Ruhul Ameen, Akif Islam, Ayesha Siddiqua, Abu Saleh Musa Miah, Jungpil Shin ·

    Quantifying Affective Bias in Low-Resource Media: Large-Scale Emotion Profiling of Bengali Headlines

    arXiv:2510.17252v2 Announce Type: replace Abstract: News media can influence readers not only through the events they report but also through the emotional tone used to present them. This issue is especially important in digital news environments, where headlines often shape firs…

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