Data Science

Resisting our Data Doppelgangers: A Proposal for Unpacking the Dangers of Data-Driven Fertility Advertising With Data Science Tools

December 7, 2021

Introduction

When Janet Vertasi, a sociology professor of technology at Princeton, learned of her pregnancy, she decided to conduct a personal experiment. She hid her pregnancy from the internet for nine months. This meant only sharing her pregnancy with close friends and family, using her own personal server while making purchases on Amazon and even opting to use cash For many of her transactions. During this time Amazon mistook her as a “suspicious customer” (Vertasi 2014, Gray 2014). Recall another incident of how Target found out about a...

A Beginner’s Guide to the Bootstrap

November 22, 2021

What is the bootstrap method?

If you take a quantitative methods course here at Berkeley, chances are that you will learn how to perform a bootstrap. As an introductory data science instructor, it’s one of my favorite topics to teach, not just because it’s a powerful and useful tool, but also because it’s incredibly intuitive. In short, the bootstrap -- also known as resampling with replacement -- allows us to generate a distribution of sample statistics given only a single sample, estimating sampling error.The name of this method...

Stumbling Upon Data Sonification When I Fused My Passion for Music with Coding

November 16, 2021

Like many graduate students from the MIDS program who are also full-time working professionals, I return to campus to seek knowledge and satisfy my intellectual curiosity in information and data science. It has become a part of a lifelong learning pursuit that enables me to constantly apply what I learn back into the real world. Along the way, I never forget that it is also important to have fun with science by combining new knowledge with my own passions in arts and music in whatever ways possible. For nearly a decade, I have been helping clients in...

Rural vs. Urban: Using Python to Explore Legislative Data

November 8, 2021

Before COVID-19, becoming a data scientist was never on my radar. As a policy analyst for the California Research Bureau, a legislative research and reference section of the California State Library, I’ve worked on a variety of projects and requests. For the last 8 years, my work has focused on producing timely, confidential ...

Assessing the Effectiveness of a Social Norms-Based Sexual Violence Prevention Digital Campaign on the UC Berkeley Campus

August 31, 2021
In collaboration with the prevention team at the PATH To Care Center (PTC) at the University of California, Berkeley, we experimentally assess the effectiveness of a sexual violence & sexual harassment (SVSH) prevention social media campaign on perceived social norms. Content Warning: This blog post mentions sexual violence & sexual harassment (SVSH)

Project HOME: Modeling and Mapping Eviction Rates in California

August 18, 2021

6 months ago, the D-Lab community made possible a connection between the UC Berkeley School of Information, D-Lab Data Science Fellows, and the Urban Displacement Project (UDP). A summer of brainstorming, collaboration, and multiple Zoom sessions later, the team at Project HOME is excited to present our 5th Year Master of Information and Data...

Julia Lane, Ph.D.

Guest Speaker
Professor at the NYU Wagner Graduate School of Public Service
Professor at the NYU Center for Urban Science and Progress
NYU Provostial Fellow for Innovation Analytics

Julia Lane is a Professor at the NYU Wagner Graduate School of Public Service, at the NYU Center for Urban Science and Progress, and a NYU Provostial Fellow for Innovation Analytics. She cofounded the Coleridge Initiative, whose goal is to use data to transform the way governments access and use data for the social good through training programs, research projects and a secure data facility. The approach is attracting national attention, including the ...

What to do about Fairness in Machine Learning?

April 7, 2020

How many thousands of machine learning applications have been developed and gone to market in recent years? Feeding vast amounts of data into software to make decisions for us is a social paradigm the 21st century is embracing to the fullest.

I’m a graduate student of public health, but have a long history as a social worker, student of psychology, literature and the human condition. Since early childhood, one thing I have always been is a science fiction fanatic: human, and societal relationships with technology have fascinated me to the core since before I can remember.

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The Importance of Design Plans for Data Science

April 20, 2021

Since becoming a Data Fellow at the D-Lab, I have had the opportunity to assist many talented social scientists through the D-Lab’s Consulting service. A regular consulting request is to help with the research design for a new project. These requests are understandable. For empirical researchers, a high-quality research design makes or breaks a research project. In this post, I suggest a few benefits of writing a skeleton design plan before writing any code whatsoever.

One of the exciting aspects...