Spotting Controversy With NLP

published 19.05.2020 02:00

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The ESG controversy model, trained using approximately 30,000 "positive" articles that Refinitiv analysts had already annotated, was crucial and used alongside a corresponding set of negative examples.

For a specific company, by examining each of the ESG topics, the analysts decide whether the article suggests controversy or not for that topic.

Using machine learning and natural language processing (NLP), Tim Nugent's team has trained a model to review a news stream and triage news stories for potential ESG controversies.

The Refinitiv Labs team has used machine learning and NLP to positive effect, allowing the company's ESG analysts to be more productive and efficient.

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