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Hendrik Erz is a PhD student at Linköping University, specializing in measurement culture. His research employs deep learning models to extract patterns from textual data, particularly focusing on U.S. Congressional Records, which contain a vast resource of text spanning from 1873 to the present. Through the use of computational tools, he aims to make sense of large amounts of textual data to uncover signals that help understand culture. His PhD project is centered on understanding the ideas that shape individuals' actions, developing measurements, and identifying cues within the textual data. Currently, he is engaged in applying deep learning models, specifically neural networks, to analyze this extensive textual corpus.
Requirements are standardized across the Faculty of Science and Engineering (Institute of Technology) for international Master's programs.