Text Analysis

Twitter Text Analysis: A Friendly Introduction, Part 2

March 7, 2023

Twitter logo under magnifying glass surrounded by chart and tool icons

The code for this blog post is available in this GitHub repository. You can also follow along in this ...

Twitter Text Analysis: A Friendly Introduction

October 25, 2022

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...

Python Text Analysis: Topic Modeling

March 29, 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.

Python Text Analysis: Word Embeddings

April 5, 2023, 2:00pm
How can we use neural networks to create meaningful representations of words? The bag-of-words is limited in its ability to characterize text, because it does not utilize word context.

Aaron Culich

Consulting Drop-In Hours: By appointment only

Consulting Areas: Python, R, SQL, APIs, Cloud & HPC Computing, Databases & SQL, Bash or Command Line, Git or Github

Quick-tip: the fastest way to speak to a consultant is to first submit a request and then ...

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.

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...

CANCELED: Python Text Analysis: Word Embeddings

November 17, 2022, 12:00pm
How can we use neural networks to create meaningful representations of words? The bag-of-words is limited in its ability to characterize text, because it does not utilize word context.
Registration is unavailable.

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.
Registration is unavailable.