中美贸易战下的中国it公司:计算政治传播视角

Yekai Xu, Mingqing Xie
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引用次数: 0

摘要

基于社交媒体文本大数据分析的计算政治传播为理解公众对全球政治事件的看法和参与提供了一种范式。本研究回顾了社会和数据科学家之前的努力,并提供了一个演示来展示计算政治传播的潜力。为了描述围绕中美紧张局势的在线政治交流动态,并更好地了解美中权力斗争,我们收集了2020年3月至2021年3月期间全球大量用户生成的推特数据。中国IT巨头(华为、腾讯、字节跳动)和主要英语国家(美国、英国、加拿大、澳大利亚、新西兰、印度、巴基斯坦)被选为过滤推文的关键词。自动对推文进行情感分析。研究发现,关于某些国家和公司的辩论的受欢迎程度是不平衡的,可能是由事件引发的。此外,所有这些公司的话语不是相互隔离的,而是相互交织的。预计未来的研究可以应用更细粒度、分类和自动化的情感和主题分析,以展示在线民意的全景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CHINESE IT COMPANIES UNDER U.S.-CHINA TRADE WAR: A COMPUTATIONAL POLITICAL COMMUNICATION PERSPECTIVE
Computational political communication, based on big data analytics of social media texts, provides a paradigm for understanding the public's view of and engagement with political events worldwide. This study reviews previous efforts by social and data scientists and offers a demo to show the potential of computational political communication. To characterize online political communication dynamics surrounding U.S.-China tensions and gain a better understanding of the U.S.-China power struggle, a vast amount of user-generated Twitter data is compiled from March 2020 to March 2021 globally. Chinese IT giants (Huawei, Tencent, and ByteDance) and major English-speaking countries (the United States, United Kingdom, Canada, Australia, New Zealand, India, and Pakistan) are chosen as keywords for filtering the tweets gathered. Sentiment analysis of the tweets is carried out automatically. It is found that the popularities of debates regarding certain nations and companies are uneven and might be triggered by events. Furthermore, rather than being segregated, the discourses of all of these companies are intertwined. It is expected that future studies can apply more fine-grained, categorized, and automated sentiment and topic analysis to show a panorama of online public opinion.
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