This study provides an in-depth analysis of a Twitter dataset around AstraZeneca COVID vaccine development released as a part of Grand Challenge, North American Social Network Conference, 2021. In brief, we show: i) the presence of malicious and low credibility information sources shared on Twitter messages in multiple languages, ii) the malicious URLs, often in shortened forms, are increasingly hosted in content delivery networks and shared cloud hosting infrastructures not only to improve reach but also to avoid being detected and blocked, iii) potential signs of coordination to promote both malicious and low credibility URLs on Twitter. We use a null model and several statistical tests to identify meaningful coordination behavior.

中文翻译：

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Twitter上COVID-19期间的恶意和低可信度URL

这项研究提供了有关阿斯利康COVID疫苗开发的Twitter数据集的深入分析，该数据集是2021年北美社交网络大会“盛大挑战”的一部分发布的。简而言之，我们表明：i）存在恶意和低信誉信息源在Twitter消息上以多种语言共享，ii）恶意URL（通常以缩短的形式）越来越多地托管在内容交付网络和共享的云托管基础结构中，不仅提高了覆盖范围，而且避免了被检测和阻止的可能性，iii）潜在的迹象协调在Twitter上推广恶意和低信誉URL。我们使用空模型和几个统计测试来识别有意义的协调行为。