Current Working Groups

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.

Check the D-Lab Calendar to view and register for upcoming working group meetings. Please register so we can provide enough seating, materials, etc.

• Feb 5th: Ilya Akdemir,  JSD candidate at UC Berkeley School of Law: Privacy and data ethics in text data mining contexts

• Feb 19th: Dima Lituiev, PhD, Sr Machine Learning Scientist @ Bakar Computational Health Sciences Institute, UCSF: Learning in, from, and with Taxonomies

• Mar 5th: Ander Riutta, Institute of Data Science and Biotechnology, Gladstone Institutes in San Francisco: ML, OCR and NLP for extracting information from biological pathway figures

• Mar 19th: Adam Anderson, Mellon Postdoctoral Fellow in the Digital Humanities, UC Berkeley: AI and Archives: finding the optimal path from analog to digital

• Apr 2nd: Cody Hennesy, Journalism & Digital Media Librarian, University of Minnesota & David Naughton, Library Data and Technology, University of Minnesota: What are topic models for?

• Apr 16th: Tim Tangherlini, Professor of Danish Literature and Culture in the Dept of Scandinavian, UC Berkeley: Mining for Conspiracies: A pipeline for the discovery of conspiracy theories on social media

• Apr 30th: Kenneth Ayotte, Robert L. Bridges Professor of Law, UC Berkeley: The Cost of Conflict in Bankruptcy Reorganizations

• May 7th: Alicia Tsai, EECS PhD student at UC Berkeley: Returning to Foster Care: Revisited with Computational Text Analysis

• May 14th: Bo Zhou, Samuel Harreschou, Sixtine Lauron, James Corbitt, Master of Engineering Students at UC Berkeley: [UCSF Bakar] Enhancing physicians’ prognoses using deep learning