Adapting to Non-stationarity with Growing Expert Ensembles - Cosma Rohilla Shalizi; Abigail Z. Jacobs; Aaron Clauset (CoRR, 2011)

Detecting Friendship Within Dynamic Online Interaction Networks. - Sears A. Merritt; Abigail Z. Jacobs; Winter A. Mason; Aaron Clauset (ICWSM, 2013)

Adapting the Stochastic Block Model to Edge-Weighted Networks - Christopher Aicher; Abigail Z. Jacobs; Aaron Clauset (CoRR, 2013)

A unified view of generative models for networks: models, methods, opportunities, and challenges. - Abigail Z. Jacobs; Aaron Clauset (CoRR, 2014)

Efficiently inferring community structure in bipartite networks. - Daniel B. Larremore; Aaron Clauset; Abigail Z. Jacobs (CoRR, 2014)

Assembling thefacebook: Using Heterogeneity to Understand Online Social Network Assembly. - Abigail Z. Jacobs; Samuel F. Way; Johan Ugander; Aaron Clauset (WebSci, 2015)

Learning latent block structure in weighted networks. - Christopher Aicher; Abigail Z. Jacobs; Aaron Clauset (J. Complex Networks, 2015)

Assembly in populations of social networks. - Abigail Z. Jacobs (CoRR, 2018)

Measurement and Fairness. - Abigail Z. Jacobs; Hanna M. Wallach (CoRR, 2019)

The meaning and measurement of bias: lessons from natural language processing. - Abigail Z. Jacobs; Su Lin Blodgett; Solon Barocas; Hal Daumé III; Hanna M. Wallach (FAT*, 2020)

Internet-human infrastructures: Lessons from Havana's StreetNet. - Abigail Z. Jacobs; Michaelanne Dye (CoRR, 2020)

Measurement and Fairness. - Abigail Z. Jacobs (FAccT, 2021)

Measurement as governance in and for responsible AI. - Abigail Z. Jacobs (CoRR, 2021)

A Large-Scale Comparative Study of Informal Social Networks in Firms. - Abigail Z. Jacobs; Duncan J. Watts (Manag. Sci., 2021)

Conceptualizing Algorithmic Stigmatization. - Nazanin Andalibi; Cassidy Pyle; Kristen Barta; Lu Xian; Abigail Z. Jacobs; Mark S. Ackerman (CHI, 2023)

An Empirical Analysis of Racial Categories in the Algorithmic Fairness Literature. - Amina A. Abdu; Irene V. Pasquetto; Abigail Z. Jacobs (FAccT, 2023)

The Role of Relevance in Fair Ranking. - Aparna Balagopalan; Abigail Z. Jacobs; Asia J. Biega (SIGIR, 2023)

Report of the 1st Workshop on Generative AI and Law. - A. Feder Cooper; Katherine Lee; James Grimmelmann; Daphne Ippolito; Christopher Callison-Burch; Christopher A. Choquette-Choo; Niloofar Mireshghallah; Miles Brundage; David Mimno; Madiha Zahrah Choksi; Jack M. Balkin; Nicholas Carlini; et al. (CoRR, 2023)

The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology. - Emma Harvey; Hauke Sandhaus; Abigail Z. Jacobs; Emanuel Moss; Mona Sloane (CHI, 2024)

Algorithmic Transparency and Participation through the Handoff Lens: Lessons Learned from the U.S. Census Bureau's Adoption of Differential Privacy. - Amina A. Abdu; Lauren M. Chambers; Deirdre K. Mulligan; Abigail Z. Jacobs (FAccT, 2024)

Evaluating Generative AI Systems is a Social Science Measurement Challenge. - Hanna M. Wallach; Meera A. Desai; Nicholas Pangakis; A. Feder Cooper; Angelina Wang; Solon Barocas; Alexandra Chouldechova; Chad Atalla; Su Lin Blodgett; Emily Corvi; P. Alex Dow; Jean Garcia-Gathright; et al. (CoRR, 2024)

Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice. - A. Feder Cooper; Christopher A. Choquette-Choo; Miranda Bogen; Matthew Jagielski; Katja Filippova; Ken Ziyu Liu; Alexandra Chouldechova; Jamie Hayes; Yangsibo Huang; Niloofar Mireshghallah; Ilia Shumailov; Eleni Triantafillou; et al. (CoRR, 2024)

An archival perspective on pretraining data. - Meera A. Desai; Irene V. Pasquetto; Abigail Z. Jacobs; Dallas Card (Patterns, 2024)

Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge. - Hanna M. Wallach; Meera A. Desai; A. Feder Cooper; Angelina Wang; Chad Atalla; Solon Barocas; Su Lin Blodgett; Alexandra Chouldechova; Emily Corvi; P. Alex Dow; Jean Garcia-Gathright; Alexandra Olteanu; et al. (CoRR, 2025)