Technical Description

Web-based software utilizing Python and JavaScript to retrieve and display real-time text from the Twitter database. Rectangular, black-bordered text blocks containing fragments of social media discourse are positioned at irregular intervals across a white digital field. The system executes a deletion command where a text block containing the string ‘silence’ removes the earliest captured block containing the string ‘noise’, and vice versa. The accumulation of these blocks fluctuates based on the frequency of incoming data streams.

Text block dimensions and font sizes are scaled via natural language-processing algorithms that measure the sentiment of the text. Messages identified with positive connotations are rendered in a larger font size, while messages identified with negative connotations are rendered in a smaller font size. The overlapping arrangement of these typographic elements creates a layered composition of varying scales across the browser window.