#### Tokenization

Tokenization segments continuous text into individual units (tokens), typically words, converting unstructured text into structured format for computational analysis.

#### Options

- Lowercase: Convert all text to lowercase to treat "Text" and "text" as identical
- Remove Punctuation: Strip punctuation marks like periods, commas, quotes
- Remove Numbers: Eliminate numeric digits (keep for technical texts)
- Remove Symbols: Remove special characters (@, #, $, etc.)
- Remove URLs: Identify and remove web addresses

#### Usage

Select preprocessing options based on the analysis goals. Sentence segmentation splits text into sentences before tokenization when sentence structure is important (e.g., sentiment analysis).

Learn More: quanteda Tokens Documentation