Research Project

Exploratory Data Analysis in Social Science Research

November 14, 2023
Kamya Yadav
by Kamya Yadav. Causal inference has become the dominant endeavor for many political scientists, often at the expense of good research questions and theory building. Returning to descriptive inference – the process of describing the world as it exists – can help formulate research questions worth asking and theory that is grounded in reality. Exploratory data analysis is one method of conducting descriptive inference. It can help social science researchers find empirical patterns and puzzles that motivate their research questions, test correlations between variables, and engage with the existing literature on a topic. In this blog post, I walk through results from exploratory data analysis I conducted for my dissertation project on political ambition of women.

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.

Artificial Intelligence (AI) Systems, the Poor, and Consent: A Feminist Anti-Colonial Lens to Digitalized Surveillance

September 18, 2023
Alejandro Nuñez
By Alejandro Nuñez. Today’s digital age has created a sea of endless datafication where our everyday interactions, actions, and conversations are turned into data. The advancements of automated artificial intelligence (AI) systems, and their infrastructure in which they are created and trained on, have catapulted us into an era of consistent monitoring and surveillance.

Data for Health

Data for Health Summary

Analyzing the Perceptions of Cybersecurity Risks in Civil Society Organizations: A Survey Approach

April 5, 2022
Nikita Samarin

This post describes our work presented at the CHI 2020 Networked Privacy Workshop, a collaboration by a team of researchers affiliated with the UC Berkeley Center for Long-Term Cybersecurity (CLTC) and the International Computer Science Institute (ICSI). You can find more...

PoliPy: A Python Library for Scraping and Analyzing Privacy Policies

February 8, 2022
Nikita Samarin

In light of recent scandals involving the misuse and improper handling of personal data by large corporations, advocacy groups and regulators alike have given increased attention to the issue of consumer privacy [e.g., 1, 2, 3, 4, 5]. National and local governments have been enacting privacy legislation that requires companies to minimize the amount of data they collect, deters the collection of sensitive data, limits the purposes for which the data are used, and critically, gives users more transparency into data collection and use.

As part...

Understanding how organizational structures interact with psychology to influence academic-related behavior

September 8, 2021
Michael Ruiz
The ways in which educational organizations develop programs, approach pedagogy, and emphasize community building result in similarities and differences across different organizations’ structures. However, past research hasn’t developed a conceptual framework for understanding how differences in organizational structures might influence the educational outcomes of students from different backgrounds. The D-Lab NSF IUSE (Improving Undergraduate STEM Education) team sought to develop such a framework by leveraging past research from the fields of education, history, psychology, and sociology.

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

August 31, 2021
Swetha Pola
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)