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. 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.

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

Since 2012, Columbia Journalism School has offered a course called Frontiers of Computational Journalism for the students enrolled in their dual degree in CS and journalism. The course covers many computer science topics from the perspective of journalism, including document vector space representation, algorithmic and social story selection (recommendation algorithms), language topic models, information visualization, knowledge representation and reasoning, social network analysis, quantitative and qualitative inference, and information security. The Knight Foundation awarded $3,000,000 to Columbia University's Tow Center to continue its computational journalism program.

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