Extraction of macroeconomic indicators from texts and their semantic links for sentiment analysis

Case

Extraction of macroeconomic indicators from texts and their semantic links for sentiment analysis

Problem

There are progress reports and planned activities as well as projections and plans for the future.

Unstructured data should lead to a more structured view – texts in tables-facts.

Solution

First, markers (indicators, quantitative and qualitative characteristics, institutions, activities, social object, etc.) and then relations between them (forecasts, implemented changes, current situation, etc.) are highlighted.

Types of relations in this case get tonal color – negative, neutral, positive.

Technology stack

  • Python
  • Pytorch
  • Sklearn