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Automated Annotation of Text, Image, and Video Data
Fri, September 6, 8:00 to 9:30am, Pennsylvania Convention Center (PCC), 110BSession Submission Type: Created Panel
Session Description
This panel explores how advances in AI and other machine learning techniques can help researchers extract information from unstructured data --- including text, image, and video. The papers explore how these tools can be used to study public media representation on political figures, to annotate and extract relevant information from texts that follow different formats, and to segment images by distinguishing between image foreground and background features.
Sub Unit
Individual Presentations
GPT4 and LLaMa 2 as Expert Coders in Social Science Task - Sebastian Vallejo Vera, Western University; Joan C. Timoneda, Purdue University
Representation in Public Media: Six Years of Continuous Coverage of BBC News - Cantay Caliskan, University of Rochester; Alessio Albarello, Princeton University
Structuring Quantitative Image Analysis with Metric Depth - Christian Arnold, Cardiff University; Andreas Küpfer, Technical University of Darmstadt
What a DRAG! Data from Retrieval-Augmented Generation - Jonathan P Colner, University of California, Davis