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Michael S. Bernstein

Researcher at Stanford University

Publications -  207
Citations -  59397

Michael S. Bernstein is an academic researcher from Stanford University. The author has contributed to research in topics: Crowdsourcing & Computer science. The author has an hindex of 52, co-authored 191 publications receiving 42744 citations. Previous affiliations of Michael S. Bernstein include Association for Computing Machinery & Massachusetts Institute of Technology.

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Proceedings ArticleDOI

PingPong++: community customization in games and entertainment

TL;DR: PingPong++ as discussed by the authors is an augmented ping pong table that applies Do-It-Youself (DIY) and community contribution principles to the world of physical sports and play, and includes an API for creating new visualizations, easily recreateable hardware, an end-user interface for those without programming experience, and a crowd data API for replaying and remixing past games.
Posted Content

Atelier: Repurposing Expert Crowdsourcing Tasks as Micro-internships

TL;DR: In this article, a micro-internship platform that connects crowd interns with crowd mentors is proposed. But it does not address the issue that many workers cannot invest the time and sacrifice the earnings required to learn a new skill, and a lack of experience makes it difficult to get job offers even if they do.
Proceedings ArticleDOI

Meta: Enabling Programming Languages to Learn from the Crowd

TL;DR: Meta: a language extension for Python that allows programmers to share functions and track how they are used by a crowd of other programmers is introduced, finding that professional programmers are able to use Meta for complex tasks, and that Meta is able to find 44 optimizations and 5 bug fixes across the crowd.
Proceedings ArticleDOI

Lexicons on Demand: Neural Word Embeddings for Large-Scale Text Analysis

TL;DR: Empath is a tool that can generate and validate new lexical categories on demand from a small set of seed terms (like “bleed” and “punch” to generate the category violence) and is highly correlated with similar categories in LIWC.