關鍵在於上下文（NMF）：在華人社區媒體中建模主題信息動態

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

中華人民共和國是否透過華人散居媒體干預歐洲選舉？這個問題是一個持續進行的研究項目的基礎，該研究探討中華人民共和國對歐洲選舉的敘述如何在華人散居媒體中呈現，以及中華人民共和國新聞媒體操控的目標。為了有效且規模化地研究散居媒體，有必要使用從定量文本分析中衍生的技術，如主題建模。在本文中，我們提出了一個用於研究中國媒體信息動態的流程。首先，我們提出了KeyNMF，一種使用基於轉換器的上下文嵌入模型進行靜態和動態主題建模的新方法。我們提供了基準評估，以證明我們的方法在許多中文數據集和指標上具有競爭力。其次，我們將KeyNMF與現有方法整合，用於描述複雜系統中的信息動態。我們將此流程應用於來自五個新聞網站的數據，重點關注2024年歐洲議會選舉前的時期。我們的方法和結果證明了KeyNMF在研究中國媒體信息動態方面的有效性，為進一步解決更廣泛的研究問題奠定了基礎。

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.