Automatically flags or categorizes potentially unsafe or sensitive text (e.g., explicit or hateful content), ensuring brand standards are met.
Content moderation is an NLP task that automatically flags or categorizes text that is deemed potentially unsafe, sensitive, or inappropriate (e.g., containing explicit or hateful content). This module is crucial for maintaining brand standards and is highly useful for monitoring user-generated content, such as forum comments or social media mentions. APIs like Google Cloud NLP provide this feature.
Sources & References
Explore other NLP (Concepts & Pipeline) terms
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Emotion detection/analysis
A specialized NLP task that detects emotions like sadness, joy, fear, disgust, and anger.
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Entity Extraction (NER)
A core NLP technique aimed at extraction and classification of key information (named entities) within…
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Entity Sentiment Analysis
Combines entity analysis and sentiment analysis to determine the sentiment (positive or negative) expressed about…
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Lexical or morphological analysis
The first part of the five phases of compiler design (NLP).
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Natural Language Processing (NLP)
A field dealing with processing text; includes tasks like Entity Extraction/NER.
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Semantic Analysis
Phase 3 of NLP (compiler design) aimed at understanding the meaning in a statement. Includes…
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Sentiment Analysis
Analyzes text to identify the dominant emotional opinion (positive, negative, or neutral).
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Syntax analysis (parsing)
Phase 2 of NLP (compiler design) that analyzes grammatical structure.
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Topic Modeling
An unsupervised task (clustering) for identifying themes/topics from large sets of unstructured text, often applied…