What is Computational Journalism? What Could it Be?
Abstract: Investigative journalism is underprovided in the market, but new combinations of data and algorithms may make it easier for journalists to discover and tell the stories that hold institutions accountable. Computational journalism is a rapidly evolving field that describes stories told by, through, and about algorithms. This talk will provide an overview of how computational journalism is growing as a reporting practice and as a research field. Particular attention will be devoted to examples of work at Stanford, and the prospects for future interdisciplinary projects and partnerships that may support the production of high-quality public affairs reporting. Ideas discussed will build on research from Democracy’s Detectives: The Economics of Investigative Journalism.
About the speaker: James T. Hamilton is the Hearst Professor of Communication, Chair of the Department of Communication, and Director of the Journalism Program. His books on media markets and information provision include All the News That’s Fit to Sell: How the Market Transforms Information into News (Princeton, 2004), Regulation Through Revelation: The Origin, Politics, and Impacts of the Toxics Release Inventory Program (Cambridge, 2005), and Channeling Violence: The Economic Market for Violent Television Programming (Princeton, 1998). His most recent book, Democracy’s Detectives: The Economics of Investigative Journalism (Harvard, 2016), focuses on the market for investigative reporting. Hamilton is co-founder of the Stanford Computational Journalism Lab, Senior Fellow at the Stanford Institute for Economic Policy Research, affiliated faculty at the Brown Institute for Media Innovation, and member of the JSK Fellowships Board of Visitors.