Hyperrhiz 14

BDP (Big Data Poetry)

Jhave

Citation: , Jhave. “BDP (Big Data Poetry).” Hyperrhiz: New Media Cultures, no. 14, 2016. doi:10.20415/hyp/014.f02

Abstract: BDP (Big-Data Poetry) applies a combination of data visualization, language analytics, classification algorithms, entity recognition and part-of-speech replacement techniques to 3 corpuses: 10,557 poems from the Poetry Foundation, 57,000+ hip-hop rap songs from Ohhla.com, and over 7,000 pop lyrics. Based on these templates, a Python script generates thousands of poems per hour. Sometimes Jhave reads along with this writing machine, verbally stitching and improvising spoken poems.

Samples and Files

View Project: recreation of performance, ELO 2015, Bergen

View Project: code on GitHub (Hyperrhiz snapshot)

View Project: code on GitHub (Original BDP repo)

View Project: ELO 2015 code and data corpus (zip)

Note: Requires Python package Anaconda 2.7. To run in command line:

>> cd code/poetryFoundation/ELO_July2015/
>> python ELO2015_PERF_Creeley-Aug4th.py