AI GlossarySentiment AnalysisENTRY — Natural Language Processing
[Natural Language Processing]
Sentiment Analysis.
Determining the emotional tone or opinion expressed in text, typically positive, negative, or neutral.
In-depth explanation
01Sentiment analysis extracts subjective information from text to understand attitudes and opinions. It can be binary (positive/negative), ternary (adding neutral), or more granular. Applications include social media monitoring, customer feedback analysis, and market research. Modern approaches use pre-trained language models fine-tuned on labeled sentiment data.
Examples
02EX. 01
Product review analysis
EX. 02
Social media monitoring
EX. 03
Brand perception
More in Natural Language Processing
0301BERTBidirectional Encoder Representations from Transformers, a pre-trained language model for NLP tasks.02Named Entity Recognition (NER)Identifying and classifying named entities in text into categories like person, organization, location.03Natural Language Processing (NLP)The field of AI focused on enabling computers to understand, interpret, and generate human language.04TokenizationBreaking text into smaller units (tokens) such as words, subwords, or characters.05Word EmbeddingDense vector representations of words that capture semantic meaning and relationships.
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