2017 IJCNLP IJCNLP 2017

Roles and Success in Wikipedia Talk Pages: Identifying Latent Patterns of Behavior

Abstract

AbstractIn this work we investigate how role-based behavior profiles of a Wikipedia editor, considered against the backdrop of roles taken up by other editors in discussions, predict the success of the editor at achieving an impact on the associated article. We first contribute a new public dataset including a task predicting the success of Wikipedia editors involved in discussion, measured by an operationalization of the lasting impact of their edits in the article. We then propose a probabilistic graphical model that advances earlier work inducing latent discussion roles using the light supervision of success in the negotiation task. We evaluate the performance of the model and interpret findings of roles and group configurations that lead to certain outcomes on Wikipedia.

🌉 Interdisciplinary Bridge — Interdisciplinary and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — latent role discovery
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy