Sharing open deep learning models

URL:

Abstract:

We examine how and why trained deep learning (DL) models are shared, and by whom, and why some developers share their models while others do not. Prior research has examined sharing of data and software code, but DL models are a hybrid of the two. The results from a Qualtrics survey administered to GitHub users and academics who publish on DL show that a diverse population shares DL models, from students to computer/data scientists. We find that motivations for sharing include: increasing citation rates; contributing to the collaboration of developing new DL models; encouraging to reuse; establishing a good reputation; receiving feedback to improve the model; and personal enjoyment. Reasons for not sharing include: lack of time; thinking that their models would not be interesting for others; and not having permission for sharing. The study contributes to our understanding of motivations for participating in a novel form of peer-production.

Attachment	Size
Hicss paper2018_DalgaliCrowston.pdf	669.11 KB