Text Analysis Types

Total analysis types found:

Name Description Usefulness Interpretation
Named Entities Analysis Identifies and categorizes named entities (e.g., persons, organizations, locations) in the text. Helps in understanding the key actors, places, and organizations mentioned in the text. A list of named entities found in the text, categorized by type (e.g., person, organization, location).
Named Entities Visualization Visually represents the named entities found in the text. Provides a quick, visual overview of the key entities mentioned in the text. A visual representation (e.g., highlighted text or chart) showing the named entities and their categories.
Negation Analysis Identifies and analyzes negations in the text. Helps understand the use of negative statements and their impact on the meaning of the text. A list of negated statements and their context within the text.
NLP Analysis Performs a comprehensive Natural Language Processing analysis on the text. Provides a broad overview of various linguistic features of the text. A compilation of various NLP metrics and analyses, including sentiment, entities, syntax, etc.
Phrase Extraction Identifies and extracts meaningful phrases from the text. Helps in understanding common expressions and multi-word concepts in the text. A list of extracted phrases, possibly categorized or ranked by importance.
POS Distribution Analysis Analyzes the distribution of different parts of speech in the text. Provides insights into the grammatical structure and style of the text. A breakdown or chart showing the frequency or percentage of different parts of speech in the text.
Readability Distribution Visualization Visually represents the distribution of readability scores across the text. Provides a visual understanding of how readability varies throughout the text. A graph or chart showing how readability scores change across different parts of the text.
Readability Scores Calculates various readability metrics for the text. Helps assess the complexity and accessibility of the text for different reading levels. A set of readability scores (e.g., Flesch-Kincaid, SMOG) indicating the estimated reading level or complexity of the text.
Rhetorical Structure Analysis Analyzes the rhetorical structure and argumentation patterns in the text. Helps understand the logical flow and persuasive techniques used in the text. A breakdown of rhetorical elements and their relationships within the text.
Semantic Similarity Analysis Measures the semantic similarity between different parts of the text or between texts. Helps identify related concepts and themes within the text or between different texts. A matrix or score indicating the degree of semantic similarity between text segments.
Sentence Clustering Visualization Visually groups similar sentences in the text. Helps identify main themes and repetitive ideas in the text. A visual representation (e.g., dendrogram or scatter plot) showing clusters of semantically similar sentences.
Sentence Length Distribution Analyzes the distribution of sentence lengths in the text. Provides insights into the writing style and complexity of the text. A graph or chart showing the frequency of different sentence lengths in the text.