Textstatistieken

Textstatistieken, or text statistics, refers to the quantitative analysis of textual data. This field involves calculating various metrics to understand the characteristics and patterns within a given body of text. Common text statistics include word count, sentence count, average word length, average sentence length, and syllable count. These basic metrics can provide insights into the complexity and readability of a text.

More advanced text statistics can delve into vocabulary richness, such as type-token ratio (TTR), which measures the number of unique words (types) relative to the total number of words (tokens). Other measures focus on the frequency distribution of words, identifying the most common terms. Lexical density, a measure of the proportion of content words (nouns, verbs, adjectives, adverbs) to function words (prepositions, articles, conjunctions), is another important statistic.

Text statistics find applications in diverse areas. In natural language processing (NLP), they are used for feature extraction in machine learning models, text classification, and topic modeling. Educators and writers utilize readability scores, derived from text statistics, to assess the suitability of texts for specific audiences. Researchers in linguistics and computational social science employ text statistics to analyze large corpora of text for linguistic trends, sentiment analysis, and the study of communication patterns. The field is constantly evolving with the development of new metrics and computational methods.