The ubiquitous use of social media enables researchers to obtain self-recorded longitudinal data of individuals in real-time. Because this data can be collected in an inexpensive and unobtrusive way at scale, social media has been adopted as a “passive sensor” to study human behavior. However, such research is impacted by the lack of homogeneity in the use of social media, and the engineering challenges in obtaining such data. This paper proposes a statistical framework to leverage the potential of social media in sensing studies of human behavior, while navigating the challenges associated with its sparsity. Our framework is situated in a large-scale in-situ study concerning the passive assessment of psychological constructs of 757 information workers wherein of four sensing streams was deployed - bluetooth beacons, wearable, smartphone, and social media. Our framework includes principled feature transformation and machine learning models that predict latent social media features from the other passive sensors. We demonstrate the efficacy of this imputation framework via a high correlation of 0.78 between actual and imputed social media features. With the imputed features we test and validate predictions on psychological constructs like personality traits and affect. We find that adding the social media data streams, in their imputed form, improves the prediction of these measures. We discuss how our framework can be valuable in multimodal sensing studies that aim to gather comprehensive signals about an individual's state or situation.

Organizations often strive to recruit and retain individuals who would be a "good fit" with their core values, beliefs and practices. Person-Organization (P-O congruence is known to explain employee satisfaction, commitment and absenteeism. This paper proposes a new measure of P-O fit by empirically investigating the similarity of routine within an organization. This measure of routine fit is motivated by the theory of entrainment, which refers to the synchrony of individual and community behaviors. We use unobtrusive bluetooth sensing to examine how the concurrence of latent activity patterns is related to job performance and wellbeing. Routine fit echoes traditional constructs of congruence as it is significantly related to higher task performance and lower workplace deviance. Additionally however, it is also related to greater stress and higher arousal. Prior work in organizational psychology have used single-occasion survey instruments to infer uni-dimensional models of fit. These methods are limited by subjective perceptions of employees. In contrast, we demonstrate a data-driven and multidimensional approach to study normative routines in an organization as a measure of P-O fit. We discuss the potential of our approach in designing technologies that understand the congruence of employee routines and positively impact employee functioning at the workplace.

The focus of our approach to the usability considerations of privacy and security has been on providing people with information they can use to understand the implications of their interactions with a system, as well as, to assess whether or not a system is secure enough for their immediate needs. To this end, we have been exploring two design principles for secure interaction: visualizing system activity and integrating configuration and action. Here we discuss the results of a user study designed as a broad formative examination of the successes and failures of an initial prototype based around these principles. Our response to the results of this study has been twofold. First, we have fixed a number of implementation and usability problems. Second, we have extended our visualizations to incorporate new considerations regarding the temporal and structural organization of interactions.

In our research, we have been concerned with the question of how to make relevant features of security situations visible to users in order to allow them to make informed decisions regarding potential privacy and security problems, as well as regarding potential implications of their actions. To this end, we have designed technical infrastructures that make visible the configurations, activities, and implications of available security mechanisms. This thus allows users to make informed choices and take coordinated and appropriate actions when necessary. This work differs from the more traditional security usability work in that our focus is not only on the usability of security mechanism (e.g., the ease-of-use of an access control interface), but how security can manifest itself as part of people's interactions with and through information systems (i.e., how people experience and interpret privacy and security situations, and are enabled or constrained by existing technological mechanisms to act appropriately). In this paper, we report our experiences designing, developing, and testing two technical infrastructures for supporting this approach for usable security.