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Register a new userAutomatic Classification of Neutralization Techniques in the Narrative of Climate Change Scepticism
التصنيف التلقائي لتقنيات التحييد في سرد شكوك تغير المناخ
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تقنيات التحييد، على سبيل المثالإن رفض المسؤولية والحرمان من الضحية، يتم استخدامه في سرد شكوك تغير المناخ لتبرير عدم العمل أو تعزيز وجهة نظر بديلة.نسترحب أولا بالعلوم الاجتماعية لإدخال المشكلة في مجتمع NLP، وتقديم حبيبتي مخطط الترميز، ثم جمع التعليقات التوضيحية اليدوية من التقنيات المحايدة في النص فيما يتعلق بتغير المناخ، وتجربة النماذج القائمة على برت تحت إشراف وشبه الإشرافوبعد
Neutralisation techniques, e.g. denial of responsibility and denial of victim, are used in the narrative of climate change scepticism to justify lack of action or to promote an alternative view. We first draw on social science to introduce the problem to the community of nlp, present the granularity of the coding schema and then collect manual annotations of neutralised techniques in text relating to climate change, and experiment with supervised and semi- supervised BERT-based models.
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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.
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