Text Analysis

Python Text Analysis Fundamentals: Parts 1-2

March 28, 2022, 3:00pm
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.

Tactics for Text Mining non-Roman Scripts

April 15, 2024
Hilary Faxon, Ph.D.
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.

Twitter Text Analysis: A Friendly Introduction, Part 2

March 7, 2023
Mingyu Yuan
by Mingyu Yuan. This blog post is the second part of “Twitter Text Analysis”. The goal is to use language models such as BERT to build a classifier on tweets. Word embedding, training and test splitting, model implementation, and model evaluation are introduced in this model.

Why We Need Digital Hermeneutics

July 13, 2023
Tom van Nuenen
by Tom van Nuenen. Tom van Nuenen discusses the sixth iteration of his course named Digital Hermeneutics at Berkeley. The class teaches the practices of data science and text analysis in the context of hermeneutics, the study of interpretation. In the course, students analyze texts from Reddit communities, focusing on how these communities make sense of the world. This task combines both close and distant readings of texts, as students employ computational tools to find broader patterns and themes. The article reflects on the rise of AI language models like ChatGPT, and how these machines interpret human interpretations. The popularity and profitability of language models presents an issue for the future of open research, due to the monetization of social media data.

Unlock the Joy and Power of Reading in Language Learning

August 21, 2023
Bowen Wang-Kildegaard
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
Genevieve Smith
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.

Twitter Text Analysis: A Friendly Introduction

October 25, 2022
Mingyu Yuan

Read part 2 here.

Introduction

Text analysis techniques, including sentiment analysis, topic modeling, and named entity recognition, have been increasingly used to probe patterns in a variety of text-based documents, such as books, social media posts, and others. This blog post introduces Twitter text analysis, but is not intended to cover all of the aforementioned topics. The tutorial is broken down into two parts. In this very first post, I...

Peter Amerkhanian

Graduate Student Researcher (GSR), Instructor
Goldman School of Public Policy (GSPP)

I’m a D-Lab GSR and a graduate student in The Goldman School’s Master of Public Policy/The I School’s Graduate Certificate in Applied Data Science. I have 5 years of experience working on data problems in government and nonprofits. I’m interested in social policy, program evaluation, and computational methods. Python is my principal language, but I’ve developed experience using and teaching a variety of other tools, including R, Excel, Tableau, and JavaScript. I deeply enjoy teaching data science methods and am excited to be a part of the D-Lab.

Aniket Kesari, Ph.D.

Former D-Lab Postdoc and Senior Data Science Fellow
Berkeley Law

Aniket Kesari was a postdoc and data science fellow at D-Lab. He is currently a research fellow at NYU’s Information Law Institute, and will join the faculty of Fordham Law School in 2023. His research focuses on law and data science, with particular interests in privacy, cybersecurity, and consumer protection.

Featured D-Lab Blog Post: Introducing “A Three-Step Guide to Training Computational Social Science Ph.D. Students for...