Research Projects

Impact of Emotion Analytics on Emotion Perception

An increasing number of systems promise to provide ’emotion analytics’ about how one feels. In this work, we have explored how people construe algorithmic interpretations of emotional data in personal informatics systems. A survey (n=188) showed strong interest in automatic stress and emotion tracking, but many respondents expected these systems to provide objective measurements for their emotional experiences. A second study examined how algorithmic sensor feedback influences emotional self-judgments, by comparing three system framings of physiological ElectroDermal Activity data (EDA): Positive (“alert and engaged”), Negative (“stressed”), and Control (no frame) in a mixed-methods study with 64 participants. Despite users reporting strategies to test system outputs, users still deferred to feedback and their perceived emotions were significantly influenced by feedback frames. Some users overrode personal judgments, believing the system had access to privileged information about their emotions. Based on these findings, we explore design implications for personal informatics including risks of users trusting systems that seemingly “unlock” hidden aspects of the self. We propose design approaches that provide opportunities for future emotion-monitoring systems to exploit these framing effects, and for users to more actively construe emotional states. Results were initially shared in an ‘Intro to UX’ course lecture I gave on emotion interaction in technology (see guest talk here). Read more about our methods and results here.

Implicit Beliefs in Self-Tracking Systems

A recent critique of self-tracking tools is that they can be highly normative in terms of what are best outcomes (e.g., lose weight vs. feel physically healthy). While this is a potential problem across multiple domains of self-tracking, these can be highly problematic in the context of mood or stress tracking. Prior research in psychological has surfaced strong, paradoxical effects of setting goals for how one should ideally feel, yet these findings have not been studied in the use of everyday self-tracking tools. In progress is a 5-part study to explore issues surrounding implicit beliefs in emotion trackers. You can email me if you would like to see results so far.

Deference and Interpretations of Analytics for Emotional Well-Being

Personal Informatics (PI) systems aim to improve self-knowledge by promoting insight. This requires users to compare existing beliefs about themselves with system analytics. In this project, we have created a model of the reasoning strategies that users describe when choosing whether to trust a system interpretation of their emotions over their own initial beliefs. We are further analyzing the results of 32 user interviews and approximately 100 survey responses to understand moments of insight, where users consider themselves to have learned something new due to viewing analytics. This line of research is still in progress as we conduct follow-up studies. You can see an early set of findings in poster format here. The full analysis is in a paper currently under review for CHI 2019.

Change of Heart – Emotional Reflection to Promote Behavior Change

Preventable behaviors contribute to many life threatening health problems. Behavior change systems have been deployed to modify these, but such systems typically draw on traditional behavioral theories that overlook affect. This project examines the importance of emotional  reflection for behavior change, and useful strategies to harness its benefits. You can see a poster here. Read our CHI paper with method and results here.

Below is the presentation for CHI and IBM.

Echo – A Reflective Tool for Emotional Well-being

We have developed a personal microblogging Android and iPhone app called Echo that allows you to record and reflect on past experiences.  We call this practice, Technology Mediated Reflection (TMR).  We are interested in how TMR changes people’s lives and influences well-being.  Our research explores the intersection of human memory and emotion.  Here is a sidebar about our work in a special issue of the International Journal of Design (featured on page 12). Here is an abstract of an Echo study (from CHI’13).

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