Research

Publications, conference presentations, and posters I've given or been a part of.

Using spatial regression modeling and computational grounded theory, we find evidence that the Ring Neighbors app is often used to racially gatekeep neighborhoods through a national study of the platform's usage and a case study of Los Angeles. We ground our discussion in surveillance studies, the history of the "neighborhood watch", and studies of prosumer relations.

Dan Calacci, Jeffrey Shen, Alex (Sandy) Pentland

Submitted to CSCW 2022

We introduce a Schelling extension of a well-known mobility model that helps show that experienced income segregation is associated with people's tendency to explore new places, as well as places with visitors from different income groups. We describe these tendencies as "place exploration" and "social exploration", respectively, and find that they are nearly independent from one another. Mobility behavior plays an important role in the experienced segregation of most individuals.

Esteban Moro, Dan Calacci, Xiaowen Dong, Alex (Sandy) Pentland

Forthcoming, Nature Communications

We give concrete examples of how location data collected from mobile phones is used in the marketplace and could be used for public interest work. We offer a critique of existing privacy & risk literature that characterizes 'utility' and 'risk' as just attributes of data, rather than use. We then explore a bit about how location data collected from mobile phones by Location Based-Service providers is quite different from historical location data sources.

Dan Calacci, Alex Berke, Kent Larson, Alex (Sandy) Pentland

Oxford/LSE Connected Life 2019, Data and Disorder

We used lessons from collective intelligence of human groups to inform the design of evolutionary optimization algorithms for deep reinforcement learning tasks. Human-inspired, sparse network topologies provide a multiplicative effect on learning speed and performance in a benchmark reinforcement learning task over the state of the art.

Dhaval Adjodah, Dan Calacci, Abhimanyu Dubey, Yan Leng, Peter Krafft, Esteban Moro, and Alex (Sandy) Pentland

NIPS, Fall 2017, poster

Using high-resolution location data collected from mobile phones, we develop a novel measure of social activity-space segregation in urban space. We find that different categories of places exhibit different segregation patterns, and that exposure to people of different income and race is mediated by the median income of a users' home census tract.

Dan Calacci, Esteban Moro, Xiaowen Dong, and Alex (Sandy) Pentland

CCS 2017, talk

We developed an open-source set of tools that are capable of augmenting and measuring face to face communication between people at scale.

Dan Calacci, Oren Lederman, David Shrier, and Alex (Sandy) Pentland

SBP-BRiMS 2016, poster

We developed an open-source set of tools that are capable of augmenting and measuring face to face communication between people at scale.

Dan Calacci, Oren Lederman, David Shrier, and Alex (Sandy) Pentland

SBP-BRiMS 2016, poster

Using simple unsupervised machine learning techniques to discover the dynamics of political "framing" between parties and congresspeople. We found that Republicans tend to have higher party discipline, that they tend to talk more about economy and budget, and that Democrats have a more varied set of common vocabulary.

Oren Tsur, Dan Calacci and David Lazer

ACL 2015, talk

Using topic modeling and autoregressive distributed lag models to make sense of the public statements released by congresspeople.

Computational Journalism @ Columbia, 2014, poster

Using sentiment analysis to understand the networked naming relations between actors accused of being communists during the McCarthy era.

Dan Calacci, Oren Tsur, and David Lazer

ACL 2014, poster