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. |