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Textual Analysis

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Created 2 months ago in Other

Textual analysis is the process of examining and interpreting written, spoken, or digital text data to extract meaningful insights. It involves techniques such as natural language processing (NLP), sentiment analysis, keyword extraction, and topic modeling to understand themes, patterns, and trends in large volumes of text.

In economic and financial contexts, textual analysis is widely used to analyze policy documents, financial reports, news articles, and market sentiment, helping businesses and researchers make data-driven decisions. Common tools for textual analysis include R, Python, and specialized NLP libraries like tidytext, spaCy, and TextBlob.

Related Topics

NLP
Machine Learning