Sentiment Analysis vs Tokenization-NLP

Sentiment analysis is the systematic measurement of the overall emotional tone — positive, negative, or neutral — expressed across news, social media, and market data to gauge collective investor mood.

In natural language processing, tokenization is the process of breaking down text into smaller units called tokens—typically words, subwords, or characters—that machine learning algorithms can analyze and process systematically.