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J298 Data Journalism

From social media behavior to mortgage application denials, large amounts of information are being collated and quantified in vast and ever-growing datasets. If analyzed correctly, data can tell us a lot about society and its institutions – how they function and where they fail. Because of this, journalists now must learn how to mine datasets for stories that are compelling, authoritative, and ground-breaking. This class will teach students how to find and clean government datasets, provide them with the analytical and programming tools to quickly synthesize large amounts of information,  and find the stories in the patterns and outliers.

Emmanuel Martinez is a data reporter for Reveal, where he uses data, statistics and programming to tell stories. His most recent work examines access to homeownership and mortgage discrimination. In the past, he has reported on missing persons and unidentified decedents cases, wildfires in the western United States and water shortages in California’s Central Valley. A graduate of UC Irvine, Martinez received his master’s degree from the University of Southern California, where he studied radio and data journalism. Prior to joining Reveal, he interned for KPCC, the Los Angeles NPR affiliate, where he helped reporters acquire, clean and analyze data. Martinez is based in Reveal’s Emeryville, California, office.



Time:  Th 6:00 - 9:00

Location:  106 North Gate (Upper News)

Class Number:  10849

Section:  006

Units:  3

Length:  15 weeks

Course Material Fee:  None

Enroll Limit:  12

Restrictions & Prerequisites