The Computational Text Analysis Working Group (CTAWG) features demos, tutorials, and ongoing projects through which we are learning to use an array of computational text analysis approaches including: topic modeling, TF-IDF, dictionary methods, supervised machine learning, cosine similarity scores, words-to-vectors, grammar parsing, regular expressions, and more. Visit the CTAWG website to learn more.
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Brooks received his Ph.D. in History from UC Berkeley and was trained in Data Science at General Assembly. His work applies digital tools and methods to the study of modern cities and urban issues. At D-Lab, he teaches and consults on data analytics, machine learning, geospatial analysis, and natural language processing with Python and SQL.
I’m an interdisciplinary data scientist, with a background in Middle Eastern languages (Hebrew, Arabic, and historical languages like Sumerian, Akkadian, Assyrian and Babylonian). I’ve worked in Syria, Lebanon, Israel, and Turkey with archaeological sites and museums. My technical skills include: translation and data storytelling, data forensics (3D imaging, mapping, modeling), computational linguistics (CTA, NLP, OCR), and network analysis (SNA). My roles on campus include: Research Training Manager of the Computational Social Science Training Program; Postdoc Lecturer...