The social fMRI

Abstract

A key challenge of data-driven social science is the gathering of high quality multi-dimensional datasets. A second challenge relates to design and execution of structured experimental interventions in-situ, in a way comparable to the reliability and intentionality of ex-situ laboratory experiments. In this paper we introduce the Friends and Family study, in which a young-family residential community is transformed into a living laboratory. We employ a ubiquitous computing approach that combines extremely rich data collection in terms of signals, dimensionality, and throughput, together with the ability to conduct targeted experimental interventions with study populations. We present our mobile-phonebased social and behavioral sensing system, which has been deployed for over a year now. Finally, we describe a novel tailored intervention aimed at increasing physical activity in the subject population. Results demonstrate the value of social factors for motivation and adherence, and allow us to quantify the contribution of different incentive mechanisms.

Multimodal ambulatory sleep detection

“…Participants were recruited through email. During the ~ 30-day experiment, participants (i) wore a wrist sensor on their dominant hand (Q-sensor, Affectiva, USA) to measure 3-axis acceleration (ACC), skin conductance (SC), and skin temperature (ST) at 8 Hz; (ii) installed an Android phone application using the funf open source framework [7] to measure timing of calls, timing of short message service (SMS), location, and timing of screen-on; (iii) wore a wrist actigraphy monitor on their non-dominant hand (Motion Logger, AMI, USA) to measure activity and light exposure levels every 1 minute; and (iv) completed a sleep diary every morning to record bed time, sleep latency, wake time, and the number and timing of awakenings. The sleep diary was inspected by an experimenter every day to check completion and to obtain corrections or clarifications from the student if there were any clear errors or missing data.…”

Models of Minds

“…The Social fMRI provides a seminal example. A distributed, multimodal sensing infrastructure, implemented via mobile phones over more than a year, aimed at sensing "how things spread in [a] community, such as ideas, decisions, mood, or the seasonal flu" [2]. In this frame, both "ideas" and "the flu" are equated as properties not of individuals, but of communities and relationships.…”

Fostering parent–child dialog through automated discussion suggestions

“…All collected data included a full audio recording of the interaction, which was recorded using the on-board tablet microphone. In order to setup the collection process with the existing primer, the TinkrBook application was modified to interface with a data collection framework (Aharony et al 2011) that would record and upload audio recordings. These recordings were annotated by a professional text transcription service with one annotator per reading session.…”