关键在于上下文（NMF）：建模华人侨民媒体中的主题信息动态

Context is Key(NMF): Modelling Topical Information Dynamics in Chinese Diaspora Media

October 16, 2024

作者: Ross Deans Kristensen-McLachlan, Rebecca M. M. Hicke, Márton Kardos, Mette Thunø

cs.AI

摘要

中国是否通过华人侨民媒体干预欧洲选举？这个问题是一个正在进行的研究项目的基础，该项目探讨了中国对欧洲选举的叙事在华人侨民媒体中的呈现，以及中国新闻媒体操纵的目标。为了高效且规模化地研究侨民媒体，有必要使用源自定量文本分析的技术，比如主题建模。在本文中，我们提出了一个用于研究中国媒体信息动态的流程。首先，我们介绍了KeyNMF，这是一种使用基于转换器的上下文嵌入模型进行静态和动态主题建模的新方法。我们提供了基准评估，以证明我们的方法在多个中国数据集和指标上具有竞争力。其次，我们将KeyNMF与现有方法整合，用于描述复杂系统中的信息动态。我们将这一流程应用于来自五家新闻网站的数据，重点关注2024年欧洲议会选举前的时间段。我们的方法和结果展示了KeyNMF在研究中国媒体信息动态方面的有效性，并为进一步解决更广泛的研究问题奠定了基础。

English

Does the People's Republic of China (PRC) interfere with European elections through ethnic Chinese diaspora media? This question forms the basis of an ongoing research project exploring how PRC narratives about European elections are represented in Chinese diaspora media, and thus the objectives of PRC news media manipulation. In order to study diaspora media efficiently and at scale, it is necessary to use techniques derived from quantitative text analysis, such as topic modelling. In this paper, we present a pipeline for studying information dynamics in Chinese media. Firstly, we present KeyNMF, a new approach to static and dynamic topic modelling using transformer-based contextual embedding models. We provide benchmark evaluations to demonstrate that our approach is competitive on a number of Chinese datasets and metrics. Secondly, we integrate KeyNMF with existing methods for describing information dynamics in complex systems. We apply this pipeline to data from five news sites, focusing on the period of time leading up to the 2024 European parliamentary elections. Our methods and results demonstrate the effectiveness of KeyNMF for studying information dynamics in Chinese media and lay groundwork for further work addressing the broader research questions.