This professor uses data to reveal hidden patterns in centuries of human storytelling

David Bamman studies culture at a scale few humans ever could. An associate professor in the UC Berkeley School of Information, Bamman uses computational methods to analyze books, films and music, revealing patterns in storytelling, representation and cultural change across decades and even centuries.

In this 101 in 101 video, a series that challenges UC Berkeley faculty to explain their field in 101 seconds, he breaks down the emerging field of cultural analytics, explaining how he uses data to answer big questions about how and why we tell stories.

Cultural analytics combines computer science with the humanities, using algorithms and large datasets to ask questions that would be impossible to answer through individual reading or viewing alone. Bamman’s research examines how culture shapes people’s perceptions, and how those patterns persist over time. 

One example comes from Bamman’s analysis of 100,000 books published over the past 200 years. His team found that male characters appear roughly three times more often than female characters — a disparity that has remained remarkably consistent across two centuries. Women authors, however, tend to give equal attention to male and female characters, while male authors disproportionately center men. 

The work extends beyond literature; Bamman and his collaborators are also tracking the history of cinematic techniques in Hollywood films dating back to 1922, studying when devices like close-ups, extreme long shots and camera movement became widely adopted. Other projects analyze how narrative storytelling in popular music has evolved over the last 60 years.

For Bamman, cultural analytics isn’t about replacing critics or artists with algorithms. Instead, he sees computational analysis as a complementary tool — one that offers a broader perspective on the stories and media that influence society every day.

Watch more 101 in 101 videos featuring UC Berkeley faculty and experts here.