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Engineering open production efficiency at scale | Berkman Klein Center
Wikipedia, largely used as a synecdoche for open production generally, is a large, complex, distributed system that needs to solve a set of "open problems" efficiently in order to thrive. In this talk, I'll use the metaphor of biology as a "living system" to discuss the relationship between subsystem efficiency and the overall health of Wikipedia.  Specifically, I'll describe Wikipedia's quality control subsystem and some trade-offs that were made in order to make this system efficient through the introduction of subjective algorithms and human computation.  Finally, I'll use critiques waged by feminist HCI to argue for a new strategy for increasing the adaptive capacity of this subsystem and speak generally about improving the practice of applying subjective algorithms in social spaces.  Live demo included!
aaron  sociotechnical  Wikipedia  paramecium  research  presentation  hcds  data_science 
2 days ago by jaimoe
The key to building a data science portfolio that will get you a job
Data science project ideas aimed at people wanting to build up a Github portfolio.
Data_Science  tutorials  projects 
5 days ago by jkglasbrenner
Long Term User Engagement of Netflix & Non-Netflix Shows – Nyssa Achtyes, Spring 2015
With Netflix entering the market with its original programming, it is becoming increasingly important for networks and show-runners alike to find an answer to the following questions: which broadcast model (traditional or Netflix) enables audiences to remain consistently engaged to a show throughout the season and in the off season? Are there other factors at play which keep fans interested all year long?
hcds  ds4ux  data_science 
7 days ago by jaimoe
Conversation AI by conversationai
Our research aims to help increase participation, quality, and empathy in online conversation at scale. Our three primary areas of research are:

How might machine learning methods help online conversations?
What aspects of a conversation can machine learning understand?
What are the risks and challenges of using machine learning to assist online conversations?
ai  ml  hcds  discussion  toxicity  api  github  jigsaw  data_science 
13 days ago by jaimoe

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