Overview / Usage

The purpose of this project is to generate fun sounding academic ipsum text while also creating a template text generator with a reasonable diversity of word lengths. Most generators are either deterministic/static or do not provide much diversity of word lengths. This is actually a big problem for designers when testing templates as it can lead to broken formatting when the template text is replaced. This tool provides plenty by using a combination of common words mixed with long technical words.

Methodology / Approach

The Python Natural Language Toolkit (NLTK) was used to identify common n-grams from the abstracts of papers published in Econometrica. The words were stored in a dictionary and shuffled using Numpy. The word order of these sentences was not changed while shuffling.

Technologies Used

We used

• Intel Python
• Numpy
• NLTK
• Regular Expression
• Intel MKL
• Google Appengine

Repository

https://github.com/mwt/econ-ipsum

Other links

• Website
• Alternative To