Analyzing 10 years of startup news with Machine Learning

The article states:

"Wrap Up

... we’ve scraped hundreds of thousands of articles, created text classifiers... and gotten insights from the results. The only way to perform an analysis like this is using machine learning and natural language processing, since there’s no way we can get a person to read through and interpret 270,000 articles."

I would have to say

- there's always sampling, and

- ask or read the reports of an expert, since they live in their respective news spaces.

The categories/keywords are well known, and I believe that simple statistics would suffice to produce the type of results shown.

Of course, the text would have to be scanned and the dataset cleansed/filtered first. But those techniques predate ML/NLP.