How Pandemic Spread in News: Text Analysis Using Topic Model
This study provides an incremental analysis of news coverage and public commentary on COVID-19 for researchers interested in media studies and public perception.
This research analyzed 1127 news articles and 5563 comments from SCMP covering COVID-19 between January 20 and May 19 using an LDA topic model. The study identified dominant topics, representative documents, and inconsistencies between articles and comments regarding the pandemic's spread in news.
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.