Big Local News
Computational journalist Cheryl Phillips is leading a Big Local News team which collects, processes and shares governmental data that are hard to obtain and difficult to analyze; partners with local and national newsrooms on investigative projects across a range of topics; and makes it easy to teach best practices for finding stories within the data. The team of Stanford faculty, students and researchers is doing work to inform the public about disparities in criminal justice, the environmental and economic impacts of forest fires, local government accountability through audits, the integrity of elections at the state level, and root causes of out-of-reach home prices in local markets.
Since fall 2018, Phillips and her team have held events for reporters and editors to foster newsroom collaborations; trained dozens of journalists in the use of data that Big Local News collected and archived; and begun development of a data-sharing platform. In addition, a Big Local News course for graduate and undergraduate students at Stanford was taught for the first time and will be offered again in fall 2019. Big Local News began as the Stanford Open Policing Project, which brought to light patterns of bias in police stops of motorists. The project initially collected 250 million records from 33 states, and recently it gathered and analyzed new data showing evidence of racial discrimination at not just the state patrol level but also in local police departments. Multiple newsrooms are now requesting traffic stop data from their local governments to add to the Big Local News repository.
JSK Impact Partnerships
The JSK Impact Partnerships, an initiative of the John S. Knight Journalism Fellowships at Stanford, leverages JSK’s connections and alumni network to accelerate progress in the journalism industry and improve the quality of news and information reaching the public. It operates in parallel with the JSK Journalism Fellowships, which each year brings up to 20 diverse leaders to Stanford to work on the most urgent problems in journalism.
The work of the JSK Impact Partnerships is based on JSK’s four call-to-action themes: challenging misinformation and disinformation; holding the powerful accountable; fighting bias, intolerance and injustice; and strengthening local news. Partners include Big Local News, which JSK supported with funding to train local journalists on how to access and use data about their communities to tell compelling investigative stories; News Foundry, which provides training to journalism entrepreneurs on creating sustainable businesses; and Proyecto Inventario, which provides journalists working in Cuba data about their country that they can’t normally access due to government roadblocks or the lack of robust internet service.
Analyzing Cable TV News
Cable TV news networks make editorial choices that influence how information is provided to millions of Americans. Stanford Computer Science Professor Maneesh Agrawala and a team of researchers are using artificial intelligence-based image, audio and transcript processing techniques to analyze data from nearly a decade of 24/7 broadcasts by CNN, MSNBC and Fox News. Their mission is to help explain why some stories get told more than others, who tells these stories, and what perspectives are included or left out.
The team has annotated roughly 200,000 hours of cable TV news video spanning 2010 to 2018. With information about gender, appearance attributes such as clothing type and hair color, and audio attributes like a speaker’s volume, these annotations answer questions about visual representations in the news. How often are men onscreen vs. women? (Answer: 2.2-to-1 ratio.) Do female-hosted programs give significantly more screen time to women than male-hosted shows? (Answer: They do not.) Interactive, web-based tools will be created to enable journalists and data scientists to explore the data with ease.
Computational expertise from across Stanford can participate in a JDI Bridges program to work on journalism challenges involving reporting, storytelling, and distribution and consumption of news. The program will develop related courses spanning the university’s academic departments and organize workshops, meetings, and international conferences. It builds on the Computation + Journalism Symposium that Professor Jay Hamilton, Director of the Stanford Journalism Program, co-founded with Maneesh Agrawala in 2016.