A5049581614- Mental Health Research Topics
- Behavioral Health and Interventions
- Impact of Technology on Adolescents
- Mental Health via Writing
- Complex Network Analysis Techniques
- Personal Information Management and User Behavior
- Digital Mental Health Interventions
- Data Visualization and Analytics
- Hate Speech and Cyberbullying Detection
- Social Robot Interaction and HRI
- Sleep and related disorders
- Social and Intergroup Psychology
- Sleep and Wakefulness Research
- Circadian rhythm and melatonin
- Authorship Attribution and Profiling
- Emotion and Mood Recognition
- Speech and dialogue systems
- Personality Traits and Psychology
- Human-Automation Interaction and Safety
- Innovative Human-Technology Interaction
- Psychology of Moral and Emotional Judgment
- Physical Activity and Health
- Wikis in Education and Collaboration
- Topic Modeling
- Media Influence and Health
University of California, Irvine
2018-2022
Institute of Electrical and Electronics Engineers
2021
University of California System
2017-2020
Over the past few years, new ideological movements like Alt-Right have captured attention and concern of both mainstream media, policy makers, scholars alike. Today, methods by which right-wing extremists are radicalized increasingly taking place within social media platforms online communities. However, no research has yet investigated for proactively detecting communities that may be displaying overall warning signs mass ongoing political radicalization. In our work, we use a variety text...
Abstract Previous studies of seasonal effects on sleep have yielded unclear results, likely due to methodological differences and limitations in data size and/or quality. We measured the habits 216 individuals across U.S. over four seasons for slightly a year using objective, continuous, unobtrusive measures local weather. In addition, we controlled demographics trait-like constructs previously identified correlate with behavior. investigated weather duration, bedtime, wake time. found...
Assessing performance in the workplace typically relies on subjective evaluations, such as, peer ratings, supervisor ratings and self assessments, which are manual, burdensome potentially biased. We use objective mobile sensing data from phones, wearables beacons to study offer new insights into behavioral patterns that distinguish higher lower performers when considering roles companies (i.e., supervisors non-supervisors) different types of high tech consultancy). present initial results an...
Stress can have adverse effects on health and well-being. Informed by laboratory findings that heart rate variability (HRV) decreases in response to an induced stress response, recent efforts monitor perceived the wild focused HRV measured using wearable devices. However, it is not clear well-established association between replicates naturalistic settings without explicit inductions research-grade sensors.
Current research on building intelligent agents for aiding with productivity and focus in the workplace is quite limited, despite ubiquity of information workers across globe. In our work, we present a agent which helps users schedule block out time their calendar to important tasks, monitor intervene distractions, reflect daily mood goals single, standalone application. We created two different prototype versions agent: text-based (TB) similar UI standard chatbot, more emotionally...
Social media platforms continue to evolve as archival platforms, where important milestones in an individual's life are socially disclosed for support, solidarity, maintaining and gaining social capital, or meet therapeutic needs. However, a limited understanding of how what events (or not) prevents designing be sensitive events. We ask individuals disclose on 256 participants' year-long Facebook dataset 14K posts against their self-reported contribute codebook identify event disclosures...
Personalized predictions have shown promises in various disciplines but they are fundamentally constrained their ability to generalize across individuals. These models often trained on limited datasets which do not represent the fluidity of human functioning. In contrast, generalized capture normative behaviors between individuals lack precision predicting individual outcomes. This paper aims balance tradeoff one-for-each and one-for-all by clustering mutable conducting cluster-specific...
Twitter represents a mainstream news source for the American public, offering valuable vehicle learning how citizens make sense of pandemic health threats like Covid-19. Masking as risk mitigation measure became controversial in US. The social amplification framework offers insight into event interacts with psychological, social, institutional, and cultural communication processes to shape Covid-19 perception.
Workplace environments are characterized by frequent interruptions that can lead to stress. However, measures of stress due typically obtained through self-reports, which be affected memory and emotional biases. In this paper, we use a thermal imaging system obtain objective investigate personality differences in contexts high low interruptions. Since major source workplace is email, studied 63 participants while multitasking controlled office environment with two different email contexts:...
Assessment of individuals' job performance, personalized health and psychometric measures are domains where data-driven ubiquitous computing will have a profound impact in the near future. Existing work these focus on techniques that use data extracted from questionnaires, sensors (wearable, computer, etc.), or other traits to assess well-being cognitive attributes individuals. However, can neither predict psychological global manner nor consider challenges associated with processing often...
The ubiquitous use of social media enables researchers to obtain self-recorded longitudinal data individuals in real-time. Because this can be collected an inexpensive and unobtrusive way at scale, has been adopted as a "passive sensor" study human behavior. However, such research is impacted by the lack homogeneity media, engineering challenges obtaining data. This paper proposes statistical framework leverage potential sensing studies behavior, while navigating associated with its...
Psychometric modeling using digital data traces is a growing field of research with breadth potential applications in marketing, personalization and psychological assessment. We present novel form for user modeling: temporal patterns smartphone personal computer activity. show that some activity metrics are highly correlated certain Big Five personality metrics. then machine learning method binary classification each trait these both smartphones as model features. Our initial findings...
Virtual agent (VA) interaction is becoming more pervasive in work and home life. We present a study of text-based VA-user the context real-world job interview. Two VAs were designed with distinct personalities different genders. interviews conducted by 316 applicants for an entry-level position at financial firm. investigated how VA characteristics affect impression of, with, VA. Results show that when gender users dissimilar, perceived extroverted personable. When genders similar, tended to...
We present a design fiction, which is set in the near future as significant Mars habitation begins. Our goal creating this fiction to address current work-life issues on Earth and future. With shelter-in-place measures, established norms of productivity relaxation have been shaken. The creates an opportunity explore boundaries between work life, are changing with will continue change. includes two primary artifacts: (1) propaganda recruitment poster (2) fictional narrative account. former...
People regularly share retellings of their personal events through social media websites to elicit feedback about the reasonability actions in event's context. In this paper, we explore how learning approaches can be used toward goal classifying shared on media. We collect 13,748 community-labeled posts from /r/AmITheAsshole, a subreddit which Reddit users are voted upon by community members. build and evaluate total 21 machine models across seven types three distinct feature sets. find that...
Personal visualizations present a separate class of where users interact with their own data to draw inferences about themselves. In this paper, we study how realistic understanding personal can be gained from analyzing user interactions. We designed an interface presenting the gathered in prior and logged interactions 369 participants as they each explored data. found that spent different amounts time exploring used variety physical devices which could have affected engagement...
Assessment of job performance, personalized health and psychometric measures are domains where data-driven ubiquitous computing exhibits the potential a profound impact in future. Existing techniques use data extracted from questionnaires, sensors (wearable, computer, etc.), or other traits, to assess well-being cognitive attributes individuals. However, these can neither predict individual's psychological traits global manner nor consider challenges associated processing available, that is...