66 citations · 130 across the 5 of their papers we have counts for
5 papers
VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository
Kevin Hu, Neil Gaikwad, Michiel Bakker +7
Researchers currently rely on ad hoc datasets to train automated visualization tools and evaluate the effectiveness of visualization designs. These exemplars often lack the charact…
Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms
Snehalkumar, S. Gaikwad, Durim Morina +35
Paid crowdsourcing platforms suffer from low-quality work and unfair rejections, but paradoxically, most workers and requesters have high reputation scores. These inflated scores,…
A Voting-Based System for Ethical Decision Making
Ritesh Noothigattu, Snehalkumar 'Neil' S. Gaikwad, Edmond Awad +4
We present a general approach to automating ethical decisions, drawing on machine learning and computational social choice. In a nutshell, we propose to learn a model of societal p…
Prototype Tasks: Improving Crowdsourcing Results through Rapid, Iterative Task Design
Snehalkumar "Neil" S. Gaikwad, Nalin Chhibber, Vibhor Sehgal +26
Low-quality results have been a long-standing problem on microtask crowdsourcing platforms, driving away requesters and justifying low wages for workers. To date, workers have been…
Crowd Guilds: Worker-led Reputation and Feedback on Crowdsourcing Platforms
Mark E. Whiting, Dilrukshi Gamage, Snehalkumar S. Gaikwad +25
Crowd workers are distributed and decentralized. While decentralization is designed to utilize independent judgment to promote high-quality results, it paradoxically undercuts beha…