arXiv subjects

Nari Yoo

Publications and source records attributed to Nari Yoo.

2 recordsLinked to original sources

arXiv2026

Building and Governing AI Systems: Advancing Social Workers' Roles across the Technology Industry, Human Service Organizations, and Policy Institutions

Artificial intelligence is moving the technology sector into domains social work has long served, including crisis response, mental health care, benefits administration, vocational rehabilitation, and child welfare. Social workers meet technology teams as users of their tools, as subjects in their datasets, and as first responders to what those systems deploy, yet they study these systems from outside the settings where the decisions are made. This paper introduces the standard roles on a technology product team and the decisions each one controls, reviews the disciplines around AI-era technology together with the social work scholarship that meets each, and identifies five groups of technology decision roles social workers can hold across the technology industry, human service organizations, and policy institutions, spanning product, governance, organizational technology leadership, grantee collaboration, and policy work. Product management is our primary example. We set the nine competencies of the 2022 Educational Policy and Accreditation Standards against the tasks that role performs to show where MSW training already teaches the method the job asks for. We then specify the technical understanding these roles require, extend the profession's technology ethics from use to deployment, and close with a research agenda for the profession's technology workforce.

cs.CY↗

arXiv2026

Predicting Depressive Symptoms through Emotion Pairs within Asian American Families

Studies on intergenerational relationships between parents and children in Asian American families highlight their impact on mental health and well-being. This study investigates the role of ambivalent emotions in online narratives shared by Asian and Asian American children on the subreddit, r/Asianparentstories. By employing a BERT-based model to detect emotion at the sentence level and depressive symptoms at the post level, we analyze mixed feelings to better understand how they predict depressive symptoms. First, among 28 detectable, eight (realization, approval, sadness, anger, curiosity, annoyance, disappointment, disapproval) comprise over 50%, exhibiting significant co-occurrence among themselves and with other emotions. Second, we find the co-occurrence of multiple emotions, indicating that emotions in a single post are not limited to consistently positive or negative feelings. Finally, our findings indicate that while negative emotion pairs (e.g., confusion-grief, anger-grief) are associated with depressive symptoms, positive emotion pairs (e.g., admiration-realization, amusement-joy) negatively correlate with depressive symptoms, and combinations of ambivalent emotions indicate varied results in predicting depressive symptoms. These findings highlight the importance of automated emotion classification and the need to consider emotional ambivalence, which holds practical and clinical implications for understanding the dynamics of parent-child relationships.

cs.CY↗