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#DDJ at BabelTalk

Data journalism after hype.

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#DDJ at BabelTalk

  1. 1. Data journalism after hype @jancibulka
  2. 2. Data journalism as a trend • Hype at Google Search: “data journalism” http://www.google.com/trends/explore#q=data%20journalism
  3. 3. Data journalism and newsroom pace • journalist produce few articles per day, #ddj few per (good) month • no time for failures and death ends (way to bigger ones, scientists will tell you) • outcome known on pitch (unbiased data? not really) • gov data obtaining is a long run (no way to throw away crappy ones)
  4. 4. Data journalism and readers • in many times, charts do not helping, only illustrating (know readers how to read it?) • hiding bias and flappy work behind science • can’t interpret without understanding (what correlation 0.53 means for reader?) http://fivethirtyeight.com/datalab/do-pulitzers-help-newspapers-keep-readers/
  5. 5. Data journalism little bit hard to read http://data.blog.ihned.cz/c1-60363840-aplikace-jak-daleko-dojedete-prazskou-mhd !http://zpravy.ihned.cz/politika/c1-60996560-babis-druhy-blizko-je-i-okamura-zemanovci- by-se-do-snemovny-nedostali !http://data.blog.ihned.cz/c1-61341380-prepadeni-na-barrandove-drogy-v-holesovicich- kriminalita-optikou-mobilnich-dat
  6. 6. Data journalism and openness • open data • open code • open know-how, process… • (peer)review. lot of it. (missing community here)
  7. 7. To read • http://towcenter.org/blog/debugging-the-backlash-to-data-journalism/qz.com/ 189703/the-problem-with-data-journalism/ • http://www.niemanlab.org/2014/03/this-week-in-review-nate-silver-and-data- journalisms-critics-and-the-roots-of-diversity-problems/ • http://towcenter.org/blog/debugging-the-backlash-to-data-journalism/ Review us https://github.com/economia