Use Cases:

What kind of things can be done with a NLP-based correlation matrix?


Example questions that can be answered:

Which drugs have potential hidden relationships with other drugs?

Which public company pharmaceutical companies may have hidden relationships to drug compounds?

Example scenarios:

Pre-built sample datasets

1,002 curated cryptocurrencies correlated via NLP to 10,286 NYSE, Nasdaq & OTC Stocks:


Rows contain stock symbols. Columns contain cryptocurrencies. Dataset generation is based on public & private data, triangulation & human curation by market researchers.


110 elements & minerals correlated via NLP to 10,286 NYSE, Nasdaq & OTC Stocks:


Rows contain stock symbols. Columns contain elements & minerals. Dataset generation is based on public & private data, triangulation & human curation by market researchers.


Dataset examples:


Example use cases (with Python code):

Selected references and acknowledgements:
Pushshift.io: