Natural Language Processing (NLP)

Python Text Analysis Fundamentals: Parts 1-2

March 8, 2023, 2:00pm
This two-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.

Python Text Analysis Fundamentals: Parts 1-3

February 15, 2022, 2:00pm
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.

CANCELED: Python Text Analysis: Topic Modeling

November 15, 2022, 12:00pm
In this part, we study unsupervised learning of text data. This is a stand alone work that builds from the two-part text analysis series.

Python Text Analysis: Topic Modeling

October 16, 2023, 2:00pm
In this part, we study unsupervised learning of text data. This is a stand alone work that builds from the two-part text analysis series.

Tactics for Text Mining non-Roman Scripts

April 15, 2024
by Hilary Faxon, Ph.D. & Win Moe. Non-Roman scripts pose particular challenges for text mining. Here, we reflect on a project that used text mining alongside qualitative coding to understand the politicization of online content following Myanmar’s 2021 military coup.

Addison Pickrell

IUSE Undergraduate Advisory Board
Mathematics
Sociology

Addison is an aspiring mathematician and social scientist (Class of '27). He loves collecting books he'll never read, is an open-source and open-access advocate, and an aspiring community organizer and systems disrupter. Ask me about community-based participatory action research (CBPAR), critical pedagogy, applied mathematics, and social science.

D-Lab & Graduate Division create inclusive data science summer program

August 9, 2023
by Vanessa Navarro Rodriguez. UC Berkeley's Social Sciences D-Lab and Graduate Division created the Data Science for Social Justice Program to address underrepresentation in data science. The program teaches diverse students critical data analysis and its applications in addressing societal injustices. The 8-week free summer course for admitted University of California students focuses on Python programming, Natural Language Processing, and value-informed data practices. It aims to empower students from underrepresented backgrounds and to bridge STEM with social justice. This blog post elaborates on the program's creation and features one of the DSSJ students, Robin López, and his reasons for participating.

Unlock the Joy and Power of Reading in Language Learning

August 21, 2023
by Bowen Wang-Kildegaard. I share my story of how reading for pleasure transformed my English speaking and writing skills. This experience inspired my passion to promote the joy and power of reading to all language learners. Using natural language processing techniques, I dive into the Language Learning subreddit, revealing a trend: Learners are often highly anxious about output practices, but are generally positive about input methods like reading and listening. I then distill complex language learning theories into actionable language learning tips, emphasizing the value of extensive reading for pleasure, pointing to potential methods like using ChatGPT for customization of reading materials, and advocating for joy in the learning journey.

My Summer Exploring Data Science for Social Justice: Learnings, Tensions & Recommendations

September 5, 2023
by Genevieve Smith. This summer I joined the D-Lab hosted Data Science for Social Justice workshop at UC Berkeley diving into Python – including TF-IDF, sentiment analysis, word embeddings, and more – with a lens towards leveraging data science for social justice. My team explored a Reddit channel on abortion and used computational analysis to answer key questions related to abortion access from before versus after Roe vs. Wade was overturned. Computational social science is incredibly powerful, but I continue to grapple with tensions particularly as it relates to employing machine learning and large language in international research, and end with key recommendations for CSS practitioners.

Daniel Lobo

Computational Social Science Fellow
Sociology

Daniel Lobo is a PhD student in the Department of Sociology with an emphasis in Political Economy at UC Berkeley. He is broadly interested in how culture, or the unspoken “rules of the game,” reproduces inequality within a system of racial capitalism. At the individual level, he is interested in documenting and measuring the extent to which cultural capital and social capital enable or constrain opportunities for intergenerational mobility. At the organizational level, he is interested in documenting and measuring the extent to which culturally-based selection and promotion processes...