With the COVID-19 outbreak and the subsequent lockdown, social media became a vital communication tool. The sudden outburst of online activity influenced information spread and consumption patterns. It increases the relevance of studying the dynamics of social networks and developing data processing pipelines that allow a comprehensive analysis of social media data in the temporal dimension. This paper scopes the weekly dynamics of the information space represented by Russian social media (Twitter and Livejournal) during a critical period (massive COVID-19 outbreak and first governmental measures). The approach is twofold: a) build the time series of topic similarity indicators by identifying COVID-related topics in each week and measuring user contribution to the topic space, and b) cluster user activity and display user-topic relationships on graphs in a dashboard application. The paper describes the development of the pipeline, explains the choices made and provides a case study of the adaptation to virus control measures. The results confirm that social processes and behaviour in response to pandemic-triggered changes can be successfully traced in social media. Moreover, the adaptation trends revealed by psychological and sociological studies are reflected in our data and can be explored using the proposed method.
翻译:随着COVID-19的爆发和随后的封锁,社交媒体成为一个重要的通信工具。在线活动的突然爆发影响到信息传播和消费模式。它增加了研究社交网络动态和开发数据处理管道以便全面分析社会媒体数据的时间层面的相关性。本文介绍了俄罗斯社交媒体(Twitter和Livejournal)在关键时期(大规模COVID-19的爆发和政府的第一个措施)所代表信息空间的每周动态。这种方法有两个方面:(a) 建立主题相似性指标的时间序列,方法是在每周确定COVID相关专题并衡量用户对主题空间的贡献;(b) 集群用户活动,在仪表板应用中的图表上显示用户-主题关系。本文描述了管道的发展情况,解释了所作的选择,并提供了对病毒控制措施适应情况的案例研究。结果证实,社会媒体可以成功追踪到应对大流行病变化的社会进程和行为。此外,我们的数据中反映了心理和社会学研究揭示的适应趋势,可以使用拟议的方法加以探讨。