Computational journalism

Computational journalism can be defined as the application of computation to the activities of journalism such as information gathering, organization, sensemaking, communication and dissemination of news information, while upholding values of journalism such as accuracy and verifiability.^[1] The field draws on technical aspects of computer science including artificial intelligence, content analysis (NLP, vision, audition), visualization, personalization and recommender systems as well as aspects of social computing and information science.

History of the Field

The field emerged at the Georgia Institute of Technology in 2006 where a course in the subject was taught in 2007 and 2008. In February of 2008 Georgia Tech hosted a Symposium on Computation and Journalism which convened several hundred computing researchers and journalists in Atlanta, GA. In July of 2009, The Center for Advanced Study in the Behavioral Sciences (CASBS) at Stanford University hosted a workshop to push the field forward^[2].

Related fields

• Database journalism
• Computer-assisted reporting
• Data-driven journalism (extending the focus of data investigation to a workflow from data analysis to data visualization to storytelling based on the findings)

Resources

• DocumentCloud project
• Computational+Journalism courses at Georgia Tech
• A computational journalism reading list by Jonathan Stray of the Associated Press

References

1. ^ Nick Diakopoulos A functional roadmap for innovation in computational journalism
2. ^ James T. Hamilton Developing the Field of Computational Journalism