Human Dynamics
How social networks can influence our lives in business, health, and governance, as well as technology adoption and diffusion.
Today people leave digital breadcrumbs wherever they go, through smart phones, RFIDs, and more. The Human Dynamics group uses Reality Mining to ask how we can use this data to better organize companies, public health, and governance, by better understanding how social networks influence people when they make decisions, transmit information, adopt new technologies, or change behaviors. Our projects have already demonstrated the potential to dramatically improve the competitiveness of companies, and hint at the ability to revolutionize social environments.

Research Projects

  • Economic Decision-Making in the Wild

    Coco Krumme
    How predictable are people? We are using credit card transaction data to look at how patterns of human behavior change over time and space, and with which macroeconomic features these changes correlate. How does spending/merchant composition evolve as a region gets bigger/richer/more economically diverse? Do network features help to predict economic ones?

  • Funf: Open Sensing Framework

    Alex (Sandy) Pentland, Nadav Aharony, Wei Pan, Cody Sumter and Alan Gardner

    The Funf open sensing framework is an Android-based extensible framework for phone-based mobile sensing. The core concept is to provide a reusable set of functionalities enabling collection, uploading, and configuration for a wide range of data types. Funf Journal is an Android application for researchers, self-trackers, and anyone interested in collecting and exploring information related to the mobile device, its environment, and its user's behavior. It is built using the Funf framework and makes use of many of its built-in features.

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  • openPDS: A Privacy-Preserving Personal Data Store

    Alex (Sandy) Pentland, Yves-Alexandre de Montjoye, Samuel Siyue Wang and Alan Gardner

    With their built-in sensors, smartphones are at the forefront of personal data collection. However, personal data currently tends to be monopolized and siloed preventing companies to built innovative data-driven services. While there is substantial work on privacy and fair use of personal data, a pragmatic technical solution has yet to be realized. openPDS is a privacy-preserving implementation of an information repository which allows the user to collect, store, and give access to his data. Via an innovative framework for third-party applications to be installed, the system ensures that the sensitive data processing takes place within the user's PDS, as opposed to a third-party server. The framework allows for PDSs to engage in privacy-preserving group computation, which is used as a replacement for centralized aggregation.

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  • Sensible Organizations

    Alex (Sandy) Pentland, Benjamin Waber and Daniel Olguin Olguin
    Data mining of email has provided important insights into how organizations function and what management practices lead to greater productivity. But important communications are almost always face-to-face, so we are missing the greater part of the picture. Today, however, people carry cell phones and wear RFID badges. These body-worn sensor networks mean that we can potentially know who talks to whom, and even how they talk to each other. Sensible Organizations investigates how these new technologies for sensing human interaction can be used to reinvent organizations and management.
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  • Social Evolution

    Alex (Sandy) Pentland and Wen Dong
    How do opinions and behaviors spread in face-to-face networks? In this project, we measure the spread of political opinions, influenza and common colds, stress and loneliness, and weight changes from 320,000 hours of automated sensor data. These characteristic variations in individual behavior and network structure can be used to accurately predict outcomes across various different contexts.
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  • Social Signals in Biomedicine

    Max Little

    We are using non-invasive measurement of social signals found in voice, body movement, and location to quantify symptoms in neurological disorders such as Parkinson's Disease.

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  • The Friends and Family Study

    Alex (Sandy) Pentland Wei Pan

    The Friends and Family Study (Funf) is a long-term, mobile phone-based experiment that has transformed a graduate family community into a living lab for social-science investigation. Data from this study, collected via Android-based phones equipped with our software platform for passive data collection, will be used to look at issues including individual and group identity, real-world decision making, social diffusion, social health, and boundaries of privacy. The experiment began in March 2010, and continues through the 2011 academic year. The Funf dataset is one of the world's most comprehensive social-science datasets to date, and will allow researchers to investigate a wide range of social and behavioral questions. The Funf Android data collection software is a platform that can be reused for future studies and applications.

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