From College of Computing, Data Science, and Society
Data Discovery showcases undergraduate research projects with real-world application
By Tiffany Lohwater
Nihar Nuthikattu’s initial interest in Section 230 was kindled by following U.S. congressional hearings that included testimony from CEOs at major technology companies. A junior majoring in data science and economics at UC Berkeley, Nuthikattu said he was struck by “the stark asymmetry in technical acumen between lawmakers and digital platforms.”
Years later, Nuthikattu was considering potential research projects among the many options available to undergraduate students as part of the CDSS Data Discovery program.
He applied to participate in a project analyzing how courts interpret Section 230, a federal statute enacted as part of the Communications Decency Act. The law has been the source of frequent public debate due to the protections it provides online platforms and users, for example in the moderation of social media content...
For their research project, the students worked with Emma Lurie, a Ph.D. candidate in the School of Information at Berkeley and a J.D. candidate at Stanford Law School, to analyze how courts interpret internet platform liability. They downloaded 1,300 legal decisions to uncover patterns in how Section 230 works in practice, using their skills in large language models (LLMs) and data analysis to extract and classify key information from legal opinions.
It was Lurie’s third time participating as a project partner in the CDSS Data Discovery program, and she recommended the experience for both undergraduate students and partners...
“I get to leverage the fresh perspectives and technical skills of Berkeley data science students while having the opportunity to help them develop as data scientists, collaborators and researchers,” Lurie said.
“Research projects allow students to develop their technical skills, navigate ambiguity that is hard to replicate in the classroom environment, and build collaboration abilities with teammates on both technical and non-technical tasks – skills that will serve them well regardless of their future career.”
Emma Lurie graduated from the I School in 2025, specializing in data science and information policy.
Lurie has mentored students in the undergraduate Data Discovery program for several years, and in 2021, her team won the Ribbon of Excellence at the Data Science Discovery Showcase, and nominated Lurie for outstanding mentorship.
