Are the bots really fighting? Behind the scenes of a reproducible replication

UC Berkeley Department of Statistics: Reproducible and Collaborative Data Science

Lecture

October 10, 2017
2:00pm to 3:00pm
Berkeley, CA

A guest lecture for Fernando Perez’s STAT 159/259 course on Reproducible and Collaborative Data Science, in which I discuss issues of open science and reproducibility around our recent paper Operationalizing conflict and cooperation between automated software agents in Wikipedia: A replication and expansion of ‘Even Good Bots Fight’.

Speaker(s)

R. Stuart Geiger

BIDS Alum – Ethnographer

Former BIDS Ethnographer Stuart Geiger is now a faculty member at the University of California, San Diego, jointly appointed in the Department of Communication and the Halıcıoğlu Data Science Institute. At BIDS, as an ethnographer of science and technology, he studied the infrastructures and institutions that support the production of knowledge. He launched the Best Practices in Data Science discussion group in 2019, having been one of the original members of the MSDSE Data Science Studies Working Group. Previously, his work on Wikipedia focused on the community of volunteer editors who produce and maintain an open encyclopedia. He also studied distributed scientific research networks and projects, including the Long-Term Ecological Research Network and the Open Science Grid. In Wikipedia and scientific research, he studied topics including newcomer socialization, community governance, specialization and professionalization, quality control and verification, cooperation and conflict, the roles of support staff and technicians, and diversity and inclusion. And, as these communities are made possible through software systems, he studied how the design of software tools and systems intersect with all of these issues.  He received an undergraduate degree at UT Austin, and an MA in Communication, Culture, and Technology at Georgetown University, where he began empirically studying communities using qualitative and ethnographic methods.  As part of receiving his PhD from the UC Berkeley School of Information, he worked with anthropologists, sociologists, psychologists, historians, organizational and management scholars, designers, and computer scientists.