分析4万条推特,揭示俄乌战争中双方信息战策略差异
Propaganda and Information Dissemination in the Russo-Ukrainian War: Natural Language Processing of Russian and Western Twitter Narratives
- 用NLP和机器学习分析2022年2月至5月推文,结合人工校验
- 俄方账号多用情绪化语言制造恐惧,西方账号侧重事实与人道
- 发现账号群组行为相似,暗示有组织协调传播
乌克兰冲突不仅涉及军事对抗,更伴随显著的信息战,社交媒体平台如X(前称推特)在塑造公众认知中发挥重要作用。本文分析了自战争爆发起至2022年5月中旬共40,000条推文,涵盖宣传账号与可信账号。通过自然语言处理与机器学习算法,结合人机协同(HITL)分析,评估情感倾向并识别关键主题、话题与叙事。研究发现,双方在信息生成、传播及受众定位上采用不同策略:俄方账号频繁使用情绪化语言与虚假信息引发恐惧与不信任,而西方账号则主要聚焦事实报道与人道主义议题。聚类分析揭示出行为相似的账号群体,暗示存在有组织的协同传播。本研究有助于理解信息战动态,并为未来社交媒体在军事冲突中的影响研究提供方法支持。
原文摘要 · Abstract (English)
The conflict in Ukraine has been not only characterised by military engagement but also by a significant information war, with social media platforms like X, formerly known as Twitter playing an important role in shaping public perception. This article provides an analysis of tweets from propaganda accounts and trusted accounts collected from the onset of the war, February 2022 until the middle of May 2022 with n=40,000 total tweets. We utilise natural language processing and machine learning algorithms to assess the sentiment and identify key themes, topics and narratives across the dataset with human-in-the-loop (HITL) analysis throughout. Our findings indicate distinct strategies in how information is created, spread, and targeted at different audiences by both sides. Propaganda accounts frequently employ emotionally charged language and disinformation to evoke fear and distrust, whereas other accounts, primarily Western tend to focus on factual reporting and humanitarian aspects of the conflict. Clustering analysis reveals groups of accounts with similar behaviours, which we suspect indicates the presence of coordinated efforts. This research attempts to contribute to our understanding of the dynamics of information warfare and offers techniques for future studies on social media influence in military conflicts.
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