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新数据集解决印度政治新闻中的印地语媒体偏见问题

研究人员开发了一个新的数据集,专注于印度印地语政治新闻文章中的媒体偏见。该数据集包含来自四家主要印地语新闻机构的448篇文章,由14位专家对四种偏见类型进行了标注:选择性偏差、框架偏差、诱导点击和遗漏偏差。该项目旨在提高对印度语言媒体偏见的理解和检测能力,高标注者间一致性分数表明了数据集的可靠性。 AI

影响 该数据集能够实现对印地语媒体偏见更好的AI驱动分析,从而增进对印度信息生态系统的理解。

排序理由 该条目描述了一个用于研究目的的新学术数据集。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新数据集解决印度政治新闻中的印地语媒体偏见问题

本文如何被排名

Signal score
24 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
该条目描述了一个用于研究目的的新学术数据集。[lever_c_demoted from research: ic=1 ai=0.7]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Kushal Trivedi, Mayank Mahor, Dhruv Sanghvi, Roshni Chakraborty ·

    你读了什么就成了什么:印地语政治新闻媒体偏见数据集

    arXiv:2611.13686v1 Announce Type: new Abstract: Media bias understanding and detection remains an under-researched problem for Indian context, specifically for Indic languages, such as, Hindi, which is widely spoken in India. In this paper, we introduce a comprehensive, multi-ann…