
The Industry Documents Library is a digital archive of documents created by industries which influence public health, hosted by the University of California, San Francisco Library. This archive contains millions of video, audio, and image files from the tobacco, opioids, fossil fuel, drug, and food industries, including advertisements, legal depositions, internal marketing documents, public health campaigns, and other historical records. This session will start with a presentation and overview of the contents of the IDL and search interface. Next, we will introduce a python based, open-source stack researchers can use to analyze, transcribe, and categorize data in IDL video, audio, and image files. Although participants will have an opportunity to try out these technologies during the workshop, the primary focus will be an overview of available tools and data, and participation in the programming sections is optional. This workshop was part of the UC Love Data Week 2025 program (https://uc-love-data-week.github.io)
python, open source, ai, industry documents library, transcription technology
python, open source, ai, industry documents library, transcription technology
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
