activity
20192023
most citedKeeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems

74 citations · 87 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2023

Leveraging Recommender Systems to Reduce Content Gaps on Peer Production Platforms

Mo Houtti, Isaac Johnson, Morten Warncke-Wang +1

Peer production platforms like Wikipedia commonly suffer from content gaps. Prior research suggests recommender systems can help solve this problem, by guiding editors towards unde…

cs.CY2022★ 8 cited

"We Need a Woman in Music": Exploring Wikipedia's Values on Article Priority

Mo Houtti, Isaac Johnson, Joel Cepeda +3

Wikipedia -- like most peer production communities -- suffers from a basic problem: the amount of work that needs to be done (articles to be created and improved) exceeds the avail…

cs.HC2020

Patterns of Patient and Caregiver Mutual Support Connections in an Online Health Community

Zachary Levonian, Marco Dow, Drew Erikson +5

Online health communities offer the promise of support benefits to users, in particular because these communities enable users to find peers with similar experiences. Building mutu…

cs.HC2020★ 74 cited

Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems

C. Estelle Smith, Bowen Yu, Anjali Srivastava +3

On Wikipedia, sophisticated algorithmic tools are used to assess the quality of edits and take corrective actions. However, algorithms can fail to solve the problems they were desi…

cs.HC2019★ 5 cited

Keeping Designers in the Loop: Communicating Inherent Algorithmic Trade-offs Across Multiple Objectives

Bowen Yu, Ye Yuan, Loren Terveen +3

Artificial intelligence algorithms have been used to enhance a wide variety of products and services, including assisting human decision making in high-stakes contexts. However, th…