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

Domain:

natural language processing

Record type:

paper

Creator:

AmeIslSidMia

Host:

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 first impressions before readers open the full article. This study examines affective framing in Bengali digital journalism through corpus level emotion analysis of news headlines. Using zero shot inference with Gemma 3 4B, we analyzed 300,000 Bengali news headlines to estimate the dominant emotion and overall affective tone of each headline. The results show that negative emotion labels, particularly anger, sadness, disappointment, and fear, appear frequently in the analyzed corpus. A small pilot validation on 200 manually reviewed headlines suggests that the model can provide useful emotion estimates, although the results should be interpreted as computational estimates rather than a complete benchmark. Based on these findings, we propose a conceptual bias sensitive news interface that visualizes emotional cues across news sources and helps readers notice affective framing patterns in daily news. 5 figures, 5 tables, Accepted at 2026 International Conference on Power, Electronics, Communications, Computing, and Intelligent Infrastructure (PECCII)

Visit

arxiv.org

Tasks

emotion identification

Mining Large-Scale Low-Resource Pronunciation Data From Wikipedia

Pronunciation modeling is a key task for building speech technology in new languages, and while soli

Empowering Low-Resource Language ASR via Large-Scale Pseudo Labeling

In this study, we tackle the challenge of limited labeled data for low-resource languages in ASR, fo

ninesowngoal/low-resource-mt-bias

Code and resources for my MSc dissertation on bias in AI translation models for low-resource languag

ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages

In this multicultural age, language translation is one of the most performed tasks, and it is becomi

OpenBibleTTS: Large-Scale Speech Resources and TTS Models for Low-Resource Languages

Recent advances in neural text-to-speech (TTS) and multilingual speech generation have substantially