179 citations · 269 across the 25 of their papers we have counts for
25 papers
Thought Experiments for Conceptual Work: A New Application of a (Very) Old Method
Leah Hope Ajmani, Mo Houtti, Eric P. S. Baumer +1
In this paper, we propose thought experiments (TEs) as a crucial method for Human-Computer Interaction (HCI) researchers to engage in conceptual work. As an interdisciplinary field…
Mental Health Disorder Detection Beyond Social Media: A Systematic Review of Available Datasets
Sadiya Sayara Chowdhury Puspo, Ana-Maria Bucur, Stevie Chancellor +2
Detecting mental health disorders in a timely manner is an important societal challenge. NLP and machine learning (ML) methods used to assist with detection rely on data collected…
FedMental: Evaluating Federated Learning for Mental Health Detection from Social Media Data
Nuredin Ali Abdelkadir, Anjali Ratnam, Zeerak Talat +1
Social media text data are often used to train Machine Learning (ML) models to identify users exhibiting high-risk mental health behaviors. However, sharing this sensitive data pos…
Characterizing Delusional Spirals through Human-LLM Chat Logs
Jared Moore, Ashish Mehta, William Agnew +11
As large language models (LLMs) have proliferated, disturbing anecdotal reports of negative psychological effects, such as delusions, self-harm, and ``AI psychosis,'' have emerged…
Beyond Content Exposure: Systemic Factors Driving Moderators' Mental Health Crisis in Africa
Nuredin Ali Abdelkadir, Tianling Yang, Shivani Kapania +6
Content moderators review disturbing content to protect social media users, often at significant cost to their mental health. Recent reports document the mental health conditions o…
Unraveling Entangled Feeds: Rethinking Social Media Design to Enhance User Well-being
Ashlee Milton, Dan Runningen, Loren Terveen +2
Social media platforms have rapidly adopted algorithmic curation with little consideration for the potential harm to users' mental well-being. We present findings from design works…
Large Language Models for Mental Health: A Multilingual Evaluation
Nishat Raihan, Sadiya Sayara Chowdhury Puspo, Ana-Maria Bucur +2
Large Language Models (LLMs) have remarkable capabilities across NLP tasks. However, their performance in multilingual contexts, especially within the mental health domain, has not…
Opportunities and Barriers for AI Feedback on Meeting Inclusion in Socioorganizational Teams
Mo Houtti, Moyan Zhou, Daniel Runningen +5
Inclusion is important for meeting effectiveness, which is in turn central to organizational functioning. One way of improving inclusion in meetings is through feedback, but social…
Into the Void: Understanding Online Health Information in Low-Web Data Languages
Hellina Hailu Nigatu, Nuredin Ali Abdelkadir, Fiker Tewelde +2
Data voids--areas of the internet where reliable information is scarce or absent--pose significant challenges to online health information seeking, particularly for users operating…
Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Tasks
Luke Guerdan, Devansh Saxena, Stevie Chancellor +2
Data scientists often formulate predictive modeling tasks involving fuzzy, hard-to-define concepts, such as the "authenticity" of student writing or the "healthcare need" of a pati…
Wisdom of the Crowd, Without the Crowd: A Socratic LLM for Asynchronous Deliberation on Perspectivist Data
Malik Khadar, Daniel Runningen, Julia Tang +2
Data annotation underpins the success of modern AI, but the aggregation of crowd-collected datasets can harm the preservation of diverse perspectives in data. Difficult and ambiguo…
"I'm Petting the Laptop, Which Has You Inside It": Reflecting on Lived Experiences of Online Friendship
Seraphina Yong, Ashlee Milton, Evan Suma Rosenberg +2
Online(-only) friendships have become increasingly common in daily lives post-COVID despite debates around their mental health benefits and equivalence to ''real'' relationships. P…
Secondary Stakeholders in AI: Fighting for, Brokering, and Navigating Agency
Leah Hope Ajmani, Nuredin Ali Abdelkadir, Stevie Chancellor
As AI technologies become more human-facing, there have been numerous calls to adapt participatory approaches to AI development -- spurring the idea of participatory AI. However, t…
Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers
Jared Moore, Declan Grabb, William Agnew +4
Should a large language model (LLM) be used as a therapist? In this paper, we investigate the use of LLMs to *replace* mental health providers, a use case promoted in the tech star…
Beyond the Individual: A Community-Engaged Framework for Ethical Online Community Research
Matthew Zent, Seraphina Yong, Dhruv Bala +4
Online community research routinely poses minimal risk to individuals, but does the same hold true for online communities? In response to high-profile breaches of online community…
Observe, Ask, Intervene: Designing AI Agents for More Inclusive Meetings
Mo Houtti, Moyan Zhou, Loren Terveen +1
Video conferencing meetings are more effective when they are inclusive, but inclusion often hinges on meeting leaders' and/or co-facilitators' practices. AI systems can be designed…
Diverse Perspectives, Divergent Models: Cross-Cultural Evaluation of Depression Detection on Twitter
Nuredin Ali, Charles Chuankai Zhang, Ned Mayo +1
Social media data has been used for detecting users with mental disorders, such as depression. Despite the global significance of cross-cultural representation and its potential im…
Advancing a Consent-Forward Paradigm for Digital Mental Health Data
Sachin R. Pendse, Logan Stapleton, Neha Kumar +2
The field of digital mental health is advancing at a rapid pace. Passively collected data from user engagements with digital tools and services continue to contribute new insights…
The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data Producers
Hanlin Li, Nicholas Vincent, Stevie Chancellor +1
Many recent technological advances (e.g. ChatGPT and search engines) are possible only because of massive amounts of user-generated data produced through user interactions with com…
"All of the White People Went First": How Video Conferencing Consolidates Control and Exacerbates Workplace Bias
Mo Houtti, Moyan Zhou, Loren Terveen +1
Workplace bias creates negative psychological outcomes for employees, permeating the larger organization. Workplace meetings are frequent, making them a key context where bias may…
The Users Aren't Alright: Dangerous Mental Illness Behaviors and Recommendations
Ashlee Milton, Stevie Chancellor
In this paper, we argue that recommendation systems are in a unique position to propagate dangerous and cruel behaviors to people with mental illnesses.
All That's Happening behind the Scenes: Putting the Spotlight on Volunteer Moderator Labor in Reddit
Hanlin Li, Brent Hecht, Stevie Chancellor
Online volunteers are an uncompensated yet valuable labor force for many social platforms. For example, volunteer content moderators perform a vast amount of labor to maintain onli…
Measuring the Monetary Value of Online Volunteer Work
Hanlin Li, Brent Hecht, Stevie Chancellor
Online volunteers are a crucial labor force that keeps many for-profit systems afloat (e.g. social media platforms and online review sites). Despite their substantial role in uphol…
Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies
Nicholas Vincent, Hanlin Li, Nicole Tilly +2
Many powerful computing technologies rely on implicit and explicit data contributions from the public. This dependency suggests a potential source of leverage for the public in its…