Visualizations
Word's length boxplot
A word length boxplot is a graphical representation that displays the distribution of word lengths within a given text or dataset. It provides insights into the variability and central tendency of word lengths.
Word's length histogram
A word length histogram is a graphical representation that displays the distribution of word lengths within a given text or dataset. It provides insights into the variety and frequency of different word lengths, helping to understand the complexity and structure of the language used.
Word Frequency
Word frequency analysis is a technique used to count and analyze the occurrences of words within a text or a collection of texts. It helps identify the most common words, phrases, or terms, providing insights into the content's themes, topics, and language patterns.
Word Cloud
A word cloud is a visual representation of text data, where the size of each word indicates its frequency or importance within the text. It provides a quick and intuitive way to identify the most prominent terms in a dataset, making it easier to understand the key themes and concepts present in the text.
Sentiment Analysis
Sentiment analysis is a natural language processing technique that automatically determines the emotional tone or attitude expressed in text. It classifies written content as positive, negative, or neutral based on the opinions, emotions, and subjective information contained within the text.
Keywords extraction
Keyword extraction is a text analysis technique that automatically identifies and extracts the most important words or phrases from a document or collection of documents. It's designed to capture the key concepts, themes, and subjects that best represent the content's meaning.
Topic modelling
Topic modeling algorithms analyse the statistical patterns of word co-occurrence across your document collection. The core assumption is that documents covering similar topics will use similar vocabulary. The algorithm then groups words that frequently appear together into topics, and shows how much each document relates to each discovered topic.
