Political Science

Identifying stance in legislative discourse: a corpus-driven study of data protection laws

L. Cheng, X. Liu, et al.

This intriguing study, conducted by Le Cheng, Xiuli Liu, and Chunlei Si, delves into stance expressions in legislative discourse surrounding data protection laws across the US, EU, and China. The analysis reveals how lawmakers appear overtly neutral while subtly shaping public ideologies through covert stance expressions.

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Abstract

This study conducts a corpus-driven analysis of stance expressions in legislative discourse concerning data protection laws from the United States, the European Union, and China. Using Hyland's stance model, the researchers contrastively analyze hedging, boosting, self-mention, and attitude markers across these jurisdictions. The analysis reveals the modesty and discursive space within data protection laws, reflecting legislative values and public ideologies. The study finds a legislative tendency towards an overtly neutral appearance achieved through covert stance expressions.

Publisher

HUMANITIES AND SOCIAL SCIENCES COMMUNICATIONS

Published On

Jun 21, 2024

Authors

Le Cheng, Xiuli Liu, Chunlei Si

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