How Pandemic Spread in News: Text Analysis Using Topic Model
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Abstract (arXiv)
Researches about COVID-19 has increased largely, no matter in the biology field or the others. This research conducted a text analysis using LDA topic model. We firstly scraped totally 1127 articles and 5563 comments on SCMP covering COVID-19 from Jan 20 to May 19, then we trained the LDA model and tuned parameters based on the Cv coherence as the model evaluation method. With the optimal model, dominant topics, representative documents of each topic and the inconsistence between articles and comments are analyzed. 3 possible improvements are discussed at last.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 1 of its 13 references that are in the map. First posted on arXiv 5 Feb 2021.
Builds on
1 of 13 references.
References · 1
- 2020The COVID-19 Social Media Infodemiccited by 64
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 0; 2025: 1.
2 papers.
- 2021Contrastive Learning for Neural Topic Modelcited by 48
- 2025Continual Neural Topic Modelcited by 0
- 2025Continual Neural Topic Model21 Aug 2025
- 2021Contrastive Learning for Neural Topic Model25 Oct 2021