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

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.

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Publication Details

Journal
arXiv (Cornell University)
Published
2024-10-16
DOI
https://doi.org/10.48550/arxiv.2410.12791
Citations
2
Primary Topic
Opinion Dynamics and Social Influence
Type
article

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article

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

Mette Thunø, Ross Deans Kristensen‐McLachlan, Márton Kardos, Rebecca M. M. Hicke
2 citations
arXiv (Cornell University)
Opinion Dynamics and Social Influence
article

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

Mette Thunø, Ross Deans Kristensen‐McLachlan, Márton Kardos, Rebecca M. M. Hicke
article en
2 citations

Abstract

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.

arXiv (Cornell University)
University of Science and Culture (IR)
Netherlands eScience Center, Syddansk Universitet
Opinion Dynamics and Social Influence
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