Text Analytics of Corona Virus Covid-19 News Articles

We downloaded news articles on Covid-19 Corona Virus pandemic from Kaggle.com and uploaded the news articles data to vizrefra.com service. The results screens shows 3 types of graphs. The way VizRefra algorithm works is by relating top entities discovered with news already published in Wikipedia. 

Because we are interested to know if any of these articles has any mention of the pandemic prior to Dec 2019 when it was first discovered, we only picked an older instance of Wikipedia data base. 

2D Map of the main topics discovered: 

Zooming at the center and nearby region:

We can see on top right corner, the political and entities influence on the pandemic and how the main influencers are mentioned in the news such as Donald Trump, White House, WHO, the Indonesian president, social media and other countries. 

3D Map of the articles: 

The 3D map shows the elevation of each topic discovered and its obviously Coronavirus has the highest elevation. It has also captured related news that are considered historic on France and United States similar but smaller scale outbreak as in this zoomed region: 

Finally VizRefra lists full the entities discovered and highlights with color and code depending on its type: country, organization, people etc.