Trust is a fundamental prerequisite in the growth and sustainability of sharing economy platforms. Many of such platforms rely on actions that require trust to take place, such as entering a stranger’s car or sleeping at a stranger’s place. For this reason, understanding, measuring, and tracking trust can be of great benefit to such platforms, enabling them to identify trust behaviors, both online and offline, and identify groups which may benefit from trust-building interventions. In this work, we present the design and evaluation of a behavioral framework to measure a user’s propensity to trust others on Airbnb. We conducted an online experiment with 4,499 Airbnb users in the form of an investment game in order to capture users’ propensity to trust other users on Airbnb. Then, we used the experimental data to generate both explanatory and predictive models of trust propensity. Our contribution is a framework that can be used to measure trust propensity in sharing economy platforms via online and offline signals. We discuss which affordances need to be in place so that sharing economy platforms can get signals of trust, in addition to how such a framework can be used to inform design around trust in the short and long term.

Local community ties are an important social resource, but research shows that these ties have been declining. The social significance of location information offers an opportunity address this decline and support local community building. Through this research, we aim to understand if and how passive location sharing might be socially beneficial for communities. We conducted a deployment of MoveMeant, a location awareness app, across three different communities. Following a research through design approach, we conducted 45 interviews with users of the system and community leaders. The findings suggest that communities face issues related to lack of awareness, cohesion, and identity. We show that the app can help increase awareness of important community resources. At the same time, the findings also show a negative effect of surfacing divisions in a community, which we discuss as a intermediate, perceptual step that may contribute to the amplification effect of technology.

Awareness of and connections to a local community are important for building social capital, sharing resources, and providing physical support, but have been elusive to create in dense urban environments. We describe the design and implementation of MoveMeant, a system aimed to increase local community awareness through shared location traces. MoveMeant securely uses anonymized location data generated automatically by mobile devices to display aggregate, community-level location data. We report findings from interviews with residents in the Bronx, New York City who participated in a deployment of MoveMeant over a 6-week period. Our findings show that people use the anonymous information to make judgments about the people and places in their community, while opting to reveal their identity for third places where there is an opportunity to connect socially.

Peer-to-peer indirect exchange services, such as sharing sites that facilitate the lending and borrowing of physical goods among neighbors (such as NeighborGoods and Peerby), have not been as widely adopted as direct exchange systems, such as peer-to-peer platforms that facilitate the exchange goods and services for money (such as Uber and Airbnb). In order to understand contributing factors to this lack of adoption, we examined attitudes towards and usage of peer-to-peer resource-sharing sites among 37 residents of New York City, 9 of whom had previously used a peer-to-peer sharing site. In addition, to more deeply understand the role of trust on willingness to lend, we also conducted a survey with 195 respondents. Our findings show that people expressed concerns about violating norms of the kinds of objects suitable for sharing, about potential risks involved with entrusting a possession to somebody else, and about a dearth of available items that would be useful. Building upon previous technology acceptance models, critical mass theory, and prior research on peer economies, we propose a technology acceptance model for indirect exchange systems that includes generalized trust and ease of coordination.

In order to better understand social aspects of the short-form video watching experience, we investigated the journey to co-watching, from searching and discovering content, to choosing and experiencing videos with others. After identifying, through a large-scale survey, some of the most typical situations that bring people to YouTube, we deployed a one week-long diary study with 12 participants in which they performed a set of frequent video tasks at their leisure, half by themselves, and half with someone else. Following the diary study, we had participants reenact the diary study tasks remotely with the experimenter. We observed that users face multiple challenges on the journey to co-watching a video. They must share a device designed for an individual, use different methods for selecting videos than when by themselves, negotiate or turn-take in order to make a decision, and potentially watch a video that they do not enjoy. Along this journey, users must engage in impression management to consider how their choices might make them appear to others. We present design recommendations for remote and collocated co-watching to improve the social video watching experience.

MoodLight is an interactive ambient lighting system that responds to biosensor input related to an individual's current level of arousal. Changes in levels of arousal correspond to fluctuations in the color of light provided by the system, altering the immediate environment in ways intimately related to the user's private internal state. We use this intervention to explore personal and social implications of the ambient display of biosensor data. A design probe study conducted with university students provided the opportunity to observe MoodLight being used by individuals and dyads. Discussion of findings highlights key tensions associated with the dialectics of technology-mediated self-awareness and automated disclosure of personal information, addressing issues of agency, skepticism and uncertainty. This study provides greater understanding of the ways in which the representations of personal informatics, with a focus on ambient feedback, influence our perceptions of ourselves and those around us.