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, NLG, 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 Georgia Institute of Technology in 2006 where a course in the subject was taught by professor Irfan Essa.[2] 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.[3]

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.

Syracuse University launched a masters in computational journalism in 2015, with a mission of preparing students "to be data journalists, able to work with big data sets to organize and communicate the compelling and important news stories that might be hidden in the numbers."

Stanford University launched a Computational Journalism Lab in 2015, as well as a course titled, Computational Journalism.

In 2017, the Associated Press published a guide[4] for newsrooms to deploy artificial intelligence and computational methods, a report developed by media strategist Francesco Marconi.[5]

Computational Journalism conferences

In February 2013, the Georgia Institute of Technology held the Computational Journalism Symposium once again in Atlanta, GA.

In 2014 and 2015, Columbia University hosted the Computation + Journalism Symposium.

In 2016, Stanford University hosted the Computation + Journalism Symposium.

The Google News Lab has sponsored "Computational Journalism Research Awards" within the United States and in Europe.

Resources

Examples
gollark: Ah. I have worked out the problem. The zstandard decoder just keeps advancing the stream until, for some bizarre reason, it goes quite a lot of the way through the file.
gollark: Also, `[x+1for x in t]` might be shorter than the `map`.
gollark: Also, it *does* tuplize it.
gollark: Or shorter at all, even. Hm.
gollark: I don't know if that *is* actually shorter given indentatioforms, but it might be.

References
  1. Nick Diakopoulos A functional roadmap for innovation in computational journalism
  2. "Archived copy". Archived from the original on 2009-12-25. Retrieved 2009-12-23.CS1 maint: archived copy as title (link) 2008 Course Site
  3. James T. Hamilton Accountability Through Algorithm: Developing the Field of Computational Journalism Archived 2012-03-07 at the Wayback Machine
  4. "AP Insights | Report: How artificial intelligence will impact journalism". insights.ap.org. Retrieved 2018-03-22.
  5. "Want to bring automation to your newsroom? A new AP report details best practices". Nieman Lab. Retrieved 2018-03-22.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.