Bigram Word Cloud Animates Your Data Stories

Hands-on tutorial explaining how to create an Animated Word Cloud of bigram frequencies to display a text dataset in an MP4 video

Source: AnimatedWordCloud library. Image by Author.

Animated word cloud displays n-gram frequencies (words and consequent words in a text corpus) over time as a sequence of images in a video file. It gives greater importance to words that appear more frequently in a source text, but it scales the dataset to work with different datasets. The original visualization method uses the intuitive logic of classic word clouds and adds a time dimension to the graph. It has been designed to explore text datasets collected over multiple periods (referred to as “time-series text data”).

Michael Kane developed the core framework for animating word frequencies, and the AnimatedWordCloud (AWC) library implemented the visualization method into practice. The new release brings important updates:

• data scaling: it now works better with text datasets of different sizes and word frequencies
• extending the n_gram parameter ( = 2) to generate bigram word clouds
• efficiency improvements (saving now 220 frames for each period, improved Y axis, etc.).