PyData Global 2023

Avrahami

Abraham (Avrahami) Israeli is a research fellow at the Data Science Institute at Reichman University, focusing on research associated with NLP and social media. He is the lead of the social analytics vertical and serves as the project leader in the Arabic NLP projects.
In recent years Avrahami has taught machine learning courses in the computer science department at Reichman University.
Avrahami received his master's degree from Ben-Gurion University and his bachelor's degree from the Technion. Currently, Avrahami is a Ph.D. candidate in the Department of Software and Information Systems Engineering at Ben-Gurion University. His Ph.D. research deals with the behavior of communities and users over the web.
Before his academic path, Avrahami worked ten years in different machine-learning groups at IBM Research and Intel.


Sessions

12-07
12:30
30min
The Internet's Best Experiment Yet
Avrahami

Reddit r/place was conceived as Reddits's 2017 April Fools tongue-in-cheek experiment. A shared white canvas of million pixels (1000 x 1000) appeared in a subreddit called ''place''. Redditors could change the color of a single pixel of their choosing. Once a Redditor manipulated a pixel, he/she gets blocked by the system for a random time (5-20 minutes), effectively preventing any single Redditor from having a significant influence on the canvas. The experiment, titled by Newsweek as the Internet's best experiment yet, attracted 16.1M pixel changes performed by 1.2M unique users during 72 hours. While the expected result was total chaos, verging on white noise, the final state of the canvas contained an intricate collage of complex logos and artwork. In this talk, I present the experiment in detail, the data that were collected during the r/place experiment, and the research opportunities associated with this natural experiment. I introduce three research studies that make use of this unique dataset and settings. I share the machine-learning models we built as well as the insights gained using explainability tools, all using Python.

General Track
General Track