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English(EN) Coping in Crisis: Computational Modeling of Coping Styles in Digital Crisis Discourse During the 2023 Turkiye Earthquake

AI模型分析土耳其地震推文中应对方式

研究人员开发了一个计算模型,使用BERTurk分析2023年土耳其地震后土耳其语推文中的应对方式。该模型成功识别了三种应对方式——聚焦问题、聚焦情绪和寻求意义——宏观F1得分达到0.693。对超过一百万条推文的分析揭示了应对机制中独特的时序模式,聚焦问题应对在地震发生后立即最为普遍,而寻求意义应对随着时间的推移而增加。研究表明,愤怒与寻求意义密切相关,可能成为归咎的催化剂。 AI

影响 这项研究展示了AI在分析危机沟通方面的潜力,通过了解民众需求来援助人道主义工作。

排序理由 该集群描述了一篇学术论文,其中详细介绍了一种用于分析话语的新计算模型。

在 arXiv cs.CL 阅读 →

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AI模型分析土耳其地震推文中应对方式

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Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Research
该集群描述了一篇学术论文,其中详细介绍了一种用于分析话语的新计算模型。
Source corroboration
2 independent sources
Multiple independent publishers reporting the same story raises confidence that it's real and newsworthy.
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
109 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · \c{S}evval \c{C}ak{\i}c{\i} ·

    危机中的应对:2023年土耳其地震期间数字危机话语中应对方式的计算建模

    arXiv:2606.14420v1 Announce Type: new Abstract: How do people cope when disaster strikes and can we detect it at scale, in real time, from what they write? This study addresses that question using over one million Turkish-language tweets posted in the aftermath of the February 6,…

  2. arXiv cs.CL TIER_1 English(EN) · Şevval Çakıcı ·

    危机中的应对:2023年土耳其地震期间数字危机话语中应对方式的计算建模

    How do people cope when disaster strikes and can we detect it at scale, in real time, from what they write? This study addresses that question using over one million Turkish-language tweets posted in the aftermath of the February 6, 2023 earthquake in Turkiye, which unfolded in a…