Seminars and Events
OATH-Frames: Characterizing Online Attitudes Towards Homelessness with LLM Assistants
Event Details
Speaker: Jaspreet Ranjit, USC
Conference Room Location: ISI-MDR CR#689
Zoom Info:
https://usc.zoom.us/j/91020044560?pwd=HDtcMbDbHjlohYmDCyDO9brk7PUpeG.1
Meeting ID: 910 2004 4560
Passcode: 920185
REMINDER:
Meeting hosts only admit on-line guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom.
If you’re an outside visitor, please inform us at (nlg-seminar-host(at)isi.edu) to make us aware of your attendance so we can admit you. Specify if you will attend remotely or in person at least one business day prior to the event. Provide your: full name, job title and professional affiliation and arrive at least 10 minutes before the seminar begins.
If you do not have access to the 6th Floor for in-person attendance, please check in at the 10th floor main reception desk to register as a visitor and someone will escort you to the conference room location.
Public attitudes towards key societal issues, expressed on online media, are of immense value in policy and reform efforts, yet challenging to understand at scale. We study one such social issue: homelessness in the U.S., by leveraging the remarkable capabilities of large language models to assist social work experts in analyzing millions of posts from Twitter. We introduce a framing typology: Online Attitudes Towards Homelessness (OATH) Frames: nine hierarchical frames capturing critiques, responses and perceptions. We release annotations with varying degrees of assistance from language models, with immense benefits in scaling: 6.5× speedup in annotation time while only incurring a 3 point F1 reduction in performance with respect to the domain experts. Our experiments demonstrate the value of modeling OATH-Frames over existing sentiment and toxicity classifiers. Our large-scale analysis with predicted OATH-Frames on 2.4M posts on homelessness reveal key trends in attitudes across states, time periods and vulnerable populations, enabling new insights on the issue. Our work provides a general framework to understand nuanced public attitudes at scale, on issues beyond homelessness.
Speaker Bio
Jaspreet Ranjit is a third-year Computer Science PhD student at the University of Southern California, advised by Professor Swabha Swayamdipta in the DILL Lab and also a Student Leader of the Center for AI in Society. Her research interests lie in investigating to what extent language models can help us understand sensitive societal issues (i.e. homelessness, suicide interventions) by exploring collaborative settings between social science experts and generative models. Previously, she earned her M.S. and B.S. degree from the University of Virginia in Computer Science as a Rodman Scholar.
If speaker approves to be recorded for this NL Seminar talk, it will be posted on the USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI.
Subscribe here to learn more about upcoming seminars: https://www.isi.edu/events/
For more information on the NL Seminar series and upcoming talks, please visit:
https://www.isi.edu/research-groups-nlg/nlg-seminars/
Hosts: Jonathan May and Katy Felkner