Sentiment Analysis - Page 2

Sentiment Analysis is a computational technique used to determine and categorize the emotional tone or attitude expressed in a piece of text. It involves the use of natural language processing (NLP), machine learning, and linguistic analysis to assess whether the sentiment conveyed is positive, negative, or neutral. This analysis can be applied to various types of content, such as social media posts, customer reviews, and survey responses, helping organizations understand public perception, consumer opinions, and emotional responses to products or services. Sentiment Analysis often employs algorithms and models trained on annotated datasets to identify sentiment indicators, such as words, phrases, or contextual cues, enabling automated insights into the overall sentiment landscape.