Framing fracking

Pub Date : 2019-01-01 DOI:10.1075/JAIC.18016.MUS
Elena Musi, Mark Aakhus
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引用次数: 13

Abstract

This article offers a first large scale analysis of argumentative polylogues in the fracking controversy. It provides an empirical methodology (macroscope) that identifies, from large quantities of text data through semantic frame analysis, the many players, positions and places presumed relevant to argumentation in a controversy. It goes beyond the usual study of framing in communication research because it considers that a controversy’s communicative context is shaped, and in turn conditions, the making and defending of standpoints. To achieve these novels aims, theoretical insights from frame semantics, knowledge driven argument mining, and argumentative polylogues are combined. The macroscope is implemented using the Semafor parser to retrieve all the semantic frames present in a large corpus about fracking and then observing the distribution of those frames that semantically presuppose argumentative features of polylogue (meta-argumentative indicators). The prominent indicators are Taking_sides (indicator of “having an argument”), Evidence and Reasoning (indicators of “making an argument”). The automatic retrieval of the words associated with the core elements of the semantic frame enables the mapping of how different players, positions, and discussion venues are assembled around what is treated as disagreeable in the controversy. This knowledge driven approach to argument mining reveals prototypical traits of polylogues related to environmental issues. Moreover, it addresses a problem in conventional frame analysis common in environmental communication that focuses on the way individual arguments are presented without effective consideration of the argumentative relevance the semantics and pragmatics of certain frames operating across discourses.
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框架水力压裂
本文首次大规模分析了水力压裂法争议中争论不休的多面手。它提供了一种经验方法论(宏观),通过语义框架分析,从大量文本数据中识别出与争论中论证相关的许多参与者、立场和地点。它超越了传播学研究中通常对框架的研究,因为它认为争论的传播语境是形成的,反过来又影响了立场的形成和捍卫。为了实现这些小说的目标,本文结合了框架语义、知识驱动的论证挖掘和论证多语的理论见解。宏是使用theSemafor解析器实现的,它检索关于跟踪的大型语料库中存在的所有语义框架,然后观察这些框架的分布,这些框架在语义上预设了polylogue的论证特征(meta-argumentativeindicators)。突出的指标是“站队”(“有论点”的指标)、“证据”和“推理”(“提出论点”的指标)。自动检索与语义框架核心元素相关的单词,可以映射出不同的参与者、立场和讨论场所是如何围绕争议中被视为不愉快的内容聚集在一起的。这种知识驱动的论证挖掘方法揭示了与环境问题相关的多语者的典型特征。此外,它还解决了环境交际中常见的传统框架分析中的一个问题,即关注个体论点的呈现方式,而没有有效考虑跨话语运行的某些框架的论证相关性、语义和语用。
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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