Topic-Partitioned Multinetwork Embeddings. - Peter M. Krafft; Juston Moore; Bruce A. Desmarais; Hanna M. Wallach (NIPS, 2012)

Popularity and Performance: A Large-Scale Study. - Peter M. Krafft; Julia Zheng; Erez Shmueli; Nicolás Della Penna; Joshua B. Tenenbaum; Sandy Pentland (CoRR, 2014)

Emergent Collective Sensing in Human Groups. - Peter M. Krafft; Robert X. D. Hawkins; Alex Pentland; Noah D. Goodman; Joshua B. Tenenbaum (CogSci, 2015)

Modeling Human Ad Hoc Coordination. - Peter M. Krafft; Chris L. Baker; Alex Pentland; Joshua B. Tenenbaum (AAAI, 2016)

Sequential Voting Promotes Collective Discovery in Social Recommendation Systems. - L. Elisa Celis; Peter M. Krafft; Nathan Kobe (ICWSM, 2016)

Inferring Population Preferences via Mixtures of Spatial Voting Models. - Alison Nahm; Alex Pentland; Peter M. Krafft (SocInfo (1), 2016)

Human collective intelligence as distributed Bayesian inference. - Peter M. Krafft; Julia Zheng; Wei Pan 002; Nicolás Della Penna; Yaniv Altshuler; Erez Shmueli; Joshua B. Tenenbaum; Alex Pentland (CoRR, 2016)

Centralized, Parallel, and Distributed Information Processing during Collective Sensemaking. - Peter M. Krafft; Kaitlyn Zhou; Isabelle Edwards; Kate Starbird; Emma S. Spiro (CHI, 2017)

Bots as Virtual Confederates: Design and Ethics. - Peter M. Krafft; Michael Macy; Alex Pentland (CSCW, 2017)

A Distributed Learning Dynamics in Social Groups. - L. Elisa Celis; Peter M. Krafft; Nisheeth K. Vishnoi (PODC, 2017)

Social Bayesian Learning in the Wisdom of the Crowd. - Dhaval Adjodah; Yan Leng; Shi Kai Chong; Peter M. Krafft; Alex Pentland (CoRR, 2017)

Large-Scale Experiment on the Importance of Social Learning and Unimodality in the Wisdom of the Crowd. - Dhaval Adjodah; Shi Kai Chong; Yan Leng; Peter M. Krafft; Alex Pentland (CoRR, 2017)

A rational choice framework for collective behavior. - Peter M. Krafft (2017)

Influencing Flock Formation in Low-Density Settings. - Daniel Y. Fu; Emily S. Wang; Peter M. Krafft; Barbara J. Grosz (AAMAS, 2018)

An Experimental Study of Cryptocurrency Market Dynamics. - Peter M. Krafft; Nicolás Della Penna; Alex 'Sandy' Pentland (CHI, 2018)

Levels of Analysis in Computational Social Science. - Peter M. Krafft; Tom Griffiths 001 (CogSci, 2018)

The Wisdom of the Network: How Adaptive Networks Promote Collective Intelligence. - Alejandro Noriega Campero; Abdullah Almaatouq; Peter M. Krafft; Abdulrahman Alotaibi; Mehdi Moussaïd; Alex Pentland (CoRR, 2018)

ScamCoins, S*** Posters, and the Search for the Next BitcoinTM: Collective Sensemaking in Cryptocurrency Discussions. - Eaman Jahani; Peter M. Krafft; Yoshihiko Suhara; Esteban Moro; Alex 'Sandy' Pentland (Proc. ACM Hum. Comput. Interact., 2018)

A Bayesian Cognition Approach to Improve Data Visualization. - Yea-Seul Kim; Logan A. Walls; Peter M. Krafft; Jessica Hullman (CHI, 2019)

Keeping Rumors in Proportion: Managing Uncertainty in Rumor Systems. - Peter M. Krafft; Emma S. Spiro (CHI, 2019)

Communication Topologies Between Learning Agents in Deep Reinforcement Learning. - Dhaval Adjodah; Dan Calacci; Abhimanyu Dubey; Anirudh Goyal; Peter M. Krafft; Esteban Moro; Alex Pentland (CoRR, 2019)

Designing for Participation and Change in Digital Institutions. - Peter M. Krafft; Brian Keegan; Seth Frey (CoRR, 2019)

An Algorithmic Equity Toolkit for Technology Audits by Community Advocates and Activists. - Michael A. Katell; Meg Young; Bernease Herman; Dharma Dailey; Aaron Tam; Vivian Guetler; Corinne Bintz; Daniella Raz; P. M. Krafft (CoRR, 2019)

"This Place Does What It Was Built For": Designing Digital Institutions for Participatory Change. - Seth Frey; P. M. Krafft; Brian C. Keegan (Proc. ACM Hum. Comput. Interact., 2019)

A Simple Computational Theory of General Collective Intelligence. - Peter M. Krafft (Top. Cogn. Sci., 2019)

Municipal surveillance regulation and algorithmic accountability. - Meg Young; Michael A. Katell; P. M. Krafft (Big Data Soc., 2019)

Defining AI in Policy versus Practice. - P. M. Krafft; Meg Young; Michael A. Katell; Karen Huang; Ghislain Bugingo (AIES, 2020)

Leveraging Communication Topologies Between Learning Agents in Deep Reinforcement Learning. - Dhaval Adjodah; Dan Calacci; Abhimanyu Dubey; Anirudh Goyal; P. M. Krafft; Esteban Moro; Alex Pentland (AAMAS, 2020)

Population-level amplification of perceptual bias. - Mathew D. Hardy; Bill Thompson 001; Peter M. Krafft; Tom Griffiths 001 (CogSci, 2020)

Toward situated interventions for algorithmic equity: lessons from the field. - Michael A. Katell; Meg Young; Dharma Dailey; Bernease Herman; Vivian Guetler; Aaron Tam; Corinne Bintz; Daniella Raz; P. M. Krafft (FAT*, 2020)

Visual Narratives and Collective Memory across Peer-Produced Accounts of Contested Sociopolitical Events. - Emily Porter; P. M. Krafft; Brian Keegan (ACM Trans. Soc. Comput., 2020)

Face Mis-ID: An Interactive Pedagogical Tool Demonstrating Disparate Accuracy Rates in Facial Recognition. - Daniella Raz; Corinne Bintz; Vivian Guetler; Aaron Tam; Michael A. Katell; Dharma Dailey; Bernease Herman; P. M. Krafft; Meg Young (AIES, 2021)

An Action-Oriented AI Policy Toolkit for Technology Audits by Community Advocates and Activists. - P. M. Krafft; Meg Young; Michael A. Katell; Jennifer E. Lee; Shankar Narayan; Micah Epstein; Dharma Dailey; Bernease Herman; Aaron Tam; Vivian Guetler; Corinne Bintz; Daniella Raz; et al. (FAccT, 2021)

Accuracy-Risk Trade-Off Due to Social Learning in Crowd-Sourced Financial Predictions. - Dhaval Adjodah; Yan Leng; Shi Kai Chong; P. M. Krafft; Esteban Moro; Alex Pentland (Entropy, 2021)

Power and technology: who gets to make the decisions? - Jennifer E. Lee; Meg Young; P. M. Krafft; Michael A. Katell (Interactions, 2021)

Solidarity and Disruption Collective Organizing In Computing II. - Linda Huber; Pedro Reynolds-Cuéllar; EunJeong Cheon; P. M. Krafft; Christoph Becker 001; Danny Spitzberg; Aakash Gautam; Margaret Hughes; Alex A. Ahmed (CSCW Companion, 2022)

Confronting Power and Corporate Capture at the FAccT Conference. - Meg Young; Michael A. Katell; P. M. Krafft (FAccT, 2022)

Bias amplification in experimental social networks is reduced by resampling. - Mathew D. Hardy; Bill D. Thompson; P. M. Krafft; Thomas L. Griffiths 001 (CoRR, 2022)

Flexible social inference facilitates targeted social learning when rewards are not observable. - Robert D. Hawkins; Andrew M. Berdahl; Alex 'Sandy' Pentland; Joshua B. Tenenbaum; Noah D. Goodman; P. M. Krafft (CoRR, 2022)

Overcoming Individual Limitations Through Distributed Computation: Rational Information Accumulation in Multigenerational Populations. - Mathew D. Hardy; Peaks M. Krafft; Bill Thompson 001; Thomas L. Griffiths 001 (Top. Cogn. Sci., 2022)

Does big data serve policy? Not without context. An experiment with in silico social science. - Christopher Graziul; Alexander Belikov 003; Ishanu Chattopadhyay; Ziwen Chen; Hongbo Fang; Anuraag Girdhar; Xiaoshuang Jia; P. M. Krafft; Max Kleiman-Weiner; Candice Lewis; Chen Liang; John Muchovej; et al. (Comput. Math. Organ. Theory, 2023)

Performing Platform Governance: Facebook and the Stage Management of Data Relations. - Karen Huang; P. M. Krafft (Sci. Eng. Ethics, 2024)

From Tech Lash to Tech Fash: Strategic Reflections on a Decade of Collective Organizing in Computing. - Linda Huber; Pedro Reynolds-Cuéllar; Alicia DeVrio; Jensine Raihan; Cella Monet Sum; Lynn Dombrowski; Justine Zhang; Christoph B. Becker; Lilly Irani; P. M. Krafft; Margaret Hughes (Aarhus Conference (Adjunct), 2025)