The Climate Change Debate and Natural Language Processing

Manfred Stede, R. Patz
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引用次数: 19

Abstract

The debate around climate change (CC)—its extent, its causes, and the necessary responses—is intense and of global importance. Yet, in the natural language processing (NLP) community, this domain has so far received little attention. In contrast, it is of enormous prominence in various social science disciplines, and some of that work follows the ”text-as-data” paradigm, seeking to employ quantitative methods for analyzing large amounts of CC-related text. Other research is qualitative in nature and studies details, nuances, actors, and motivations within CC discourses. Coming from both NLP and Political Science, and reviewing key works in both disciplines, we discuss how social science approaches to CC debates can inform advances in text-mining/NLP, and how, in return, NLP can support policy-makers and activists in making sense of large-scale and complex CC discourses across multiple genres, channels, topics, and communities. This is paramount for their ability to make rapid and meaningful impact on the discourse, and for shaping the necessary policy change.
气候变化辩论与自然语言处理
围绕气候变化(CC)的争论——其范围、原因和必要的应对措施——是激烈的,具有全球重要性。然而,在自然语言处理(NLP)社区中,这一领域迄今为止很少受到关注。相比之下,它在各种社会科学学科中非常突出,其中一些工作遵循“文本即数据”范式,寻求使用定量方法来分析大量与cc相关的文本。其他研究本质上是定性的,研究CC话语中的细节、细微差别、参与者和动机。来自NLP和政治学,并回顾这两个学科的关键工作,我们讨论了社会科学方法如何为文本挖掘/NLP的进步提供信息,以及NLP如何反过来支持政策制定者和活动家理解跨多种类型、渠道、主题和社区的大规模和复杂的CC话语。这对于他们对话语产生迅速而有意义的影响以及形成必要的政策变化的能力至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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