Text Analysis

Emily Grabowski

Senior Data Science Fellow, Senior Instructor, Senior Consultant

I am a Ph.D. student in Linguistics. My research interests include understanding how our speech production and speech perception systems constrain linguistic variation, especially as it applies to the larynx. I am also interested in integrating theoretical representations of language with speech. I approach this using a broad variety of tools/methodologies, including theoretical work, experiments, and modeling. Current projects include developing a computational tool to expedite the analysis of pitch and an online perception experiment on the relationship between pitch and perceived...

Ella Belfer

Energy and Resources Group

Ella is a PhD student in the Energy and Resources Group. Her research examines water governance in a changing climate, drawing on geo-spatial techniques. Her past work includes applications of topic modelling in climate change adaptation research, and inductive coding of semi-structured interviews.

Text Analysis for Public Health

October 5, 2021
October 5th, 2021 - another day in the global pandemic. Average Joes are busy tweeting about it, politicians give interviews on the latest plans, and newspapers publish article after article on vaccination levels, case counts, and the booster shot. That’s a ton of information. So much in fact, that it would be pretty nice to have some computer assisted help to sort through it. Enter stage right: text analysis. Just what is it, and in the midst of COVID-19, how can it be used to advance public health? Text analysis is a family of analytic techniques used to identify patterns and meaning from unstructured text, that is, text that a computer can’t readily understand. Aka, most qualitative data. And there is a lot of that sort of data floating around. We’re talking tweets, Reddit posts, and emails, but also electronic health records (EHRs), books, and even academic research. You’ll probably agree that in that list alone, there’s a lot of valuable data!

Aniket Kesari, Ph.D.

Research Fellow
Berkeley Law

Aniket is a postdoctoral scholar at the D-Lab. He earned his Ph.D. from Berkeley Law, where he specialized in Law & Economics. He also holds a BA from Rutgers University – New Brunswick in Political Science and History and is a JD candidate at Yale University. His research focuses on privacy and cybersecurity law, and he is generally interested in using data science to tackle public policy problems. During his graduate career, he was a Google Public Policy Fellow, a Data Science for Social Good (DSSG) Fellow at the University of Chicago, and a Technology Policy Analyst Intern at...

Marina Blum

Data Science Fellow
School of Public Health

Marina is a master's student in the Health and Social Behavior division of the School of Public Health. She has extensive experience in ATLAS.ti and can help you get the most out of the program. She is passionate about data visualization, and is happy to help with related questions and questions on qualitative methods.

Katherine Wolf

Adjunct Fellow
Environmental Science, Policy, and Management

Doctoral student in Rachel Morello-Frosch's laboratory in the Department of Environmental Science, Policy, and Management working at the intersection of environmental epidemiology, environmental justice, and causal inference. Particularly interested in developing quantitative methods to investigate the operation of social power in environmental monitoring regimes in the United States.

Frances Leung

Data Science Fellow
School of Information

Frances Leung is a master’s student at UC Berkeley School of Information where she focuses her studies in information and data science. She has a keen interest in leveraging data-driven insights to better understand consumer behaviors and the world around us. In her professional work as a management consultant, she advises retailers and consumer businesses on digital transformation and creating web/mobile experiences that delight consumers through a human-centered approach. Frances holds a Master in Business Administration from York University, Schulich School...

Python Text Analysis Fundamentals: Parts 1-3

September 21, 2021, 10:00am
This three-part workshop series will prepare participants to move forward with research that uses text analysis, with a special focus on humanities and social science applications.

Aaron Culich

Deputy Director of D-Lab; Cyberinfrastructure Architect and Consulting Lead

Aaron Culich is a staff member at the D-Lab with expertise in Cloud Computing, High Performance Computing (HPC), Databases (SQL and NoSQL), JupyterHub and BinderHub infrastructure, and a variety of programming languages (Python, R, Java, C, C++, and more). His ongoing mission is to explore new compute possibilities, discovering useful tools and practices, and making them more accessible to researchers on campus and beyond.

George McIntire

Graduate Student Researcher (GSR)
School of Information

George is a first-year MIMS student. He specializes in Python Data Science Stack, Information Science, NLP, and Machine Learning.