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Redistributing journalism: Journalism as a data public and the politics of quantification in the newsroom

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Slides from talk at Data Power conference in Sheffield, 22-23 June 2015

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Redistributing journalism: Journalism as a data public and the politics of quantification in the newsroom

  1. 1. ! Liliana Bounegru | lilianabounegru.org | @bb_liliana Data Power Conference, University of Sheffield, 22 June 2015 Redistributing journalism: Journalism as a data public and the politics of quantification in the newsroom
  2. 2. Ongoing research project on the distributed nature of journalism in an age of big and open data and the politics of quantification in the newsroom.
  3. 3. The shift from the “digital revolution” to the “data revolution” and the “transparency revolution” has given rise to new journalism practises rooted in data, quantitative methods and computational techniques.
  4. 4. These practises are transforming not only the way news is sourced, produced and delivered but also who and what is doing the sourcing, production and delivery of journalism.
  5. 5. data infrastructures and platforms (online and government) transparency and access to information policies access to data mechanisms (proactive and reactive) government/online data collection mechanisms modes of analysis and rationales embedded in data infrastructures data tools data formats Journalism as a data public (Ruppert 2012) is constituted by complex and dynamic arrangements of actors and agencies mobilised around big and open data: journalism’s own organisational and disciplinary arrangements professional rules, norms and values in journalism journalism practises journalism genres
  6. 6. Redistributing journalism: Moving journalism studies beyond newsrooms and journalists as dominant objects of study (Deuze and Witschge forthcoming). Accounting for the distributed nature of journalistic inquiry in the age of big and open data. Accounting for the role of essential but largely overlooked human and non-human actors inside and outside the newsroom.
  7. 7. 1. Empirically mapping the heterogeneous and dynamic networks of entities through which journalism as a data public operates. 2. Investigating the role of so far understudied quantitative and computational methods for knowledge production. 3. Examining journalism product repertoires enabled by such techniques.
  8. 8. Multidisciplinary conceptual and methodological framework: journalism studies, software studies, science and technology studies, actor-network theory and digital methods.
  9. 9. Why is this important?
  10. 10. To understand the nature and role of journalism in the 21st century.
  11. 11. Redistributing journalism I: An online mapping of actors, methods, tools and product repertoires
  12. 12. Redistributing journalism II: Mobilising statistical and network analysis to enact journalism’s functions in society
  13. 13. Redistributing journalism III: Journalism product repertoires based on statistics and network analysis
  14. 14. (work in progress) ! Liliana Bounergu, University of Groningen/Ghent/Amsterdam, Jonathan Gray, University of London, University of Amsterdam, and Tommaso Venturini, SciencesPo “Narrating Networks”- Networks as storytelling devices in journalism
  15. 15. “Follow the Networks” project at! Tow Center for Digital Journalism, Columbia University.
  16. 16. http://vis.stanford.edu/files/2010-Narrative-InfoVis.pdf
  17. 17. The rise of networks
  18. 18. Mark Lombardi’s “Narrative Structures” (1990-2000)
  19. 19. Josh On’s “They Rule” (2001)
  20. 20. Muckety: http://www.muckety.com/
  21. 21. Little Sis: http://littlesis.org/
  22. 22. Networks have yet to have their
 “breakthrough moment” in journalism.
  23. 23. The lack of a clear understanding of their narrative affordances contributes to their relatively marginal position.
  24. 24. We identify common functions that networks play in journalism stories by reviewing the use of network principles, metrics and diagrams in ± 40 journalism stories.
  25. 25. What are the affordances of networks as storytelling devices? How are networks re-organising the epistemologies of the journalistic genres in which they operate?
  26. 26. Steps Survey properties of networks that are most relevant for narration. Identify the types of stories articulated around networks in journalism. Interviews with journalists who use networks. Reflect on how these affordances reconfigure the genres in which they operate.
  27. 27. A proposed classification of narrative functions for networks in journalism
  28. 28. Seven different ways in which networks have been used in journalism (The story types can be mapped back to a number of key network properties/metrics)
  29. 29. 1. Showing networks around a single actor (ego-network)
  30. 30. Washington Post, “Top Secret America” (2010)
  31. 31. Thomson Reuters, “Connected China” (2013)
  32. 32. 2. Revealing hubs or authorities (power law distribution)
  33. 33. New Scientist, “The Stem Cell Wars” (2010)
  34. 34. JoongAng Ilbo, “Park Young-joon at the Center of! President Lee Myung-bak’s Human Resources Network” (2002)
  35. 35. 3. Showing scale, complexity and topology of a network (small world)
  36. 36. Thomson Reuters, “Connected China” (2013)
  37. 37. New York Times, “Among the Oscar Contenders, a Host of Connections” (2013)
  38. 38. 4. Showing alliances and oppositions (clustering)
  39. 39. Le Monde, "2007-2011 : la cartographie de la blogosphère politique" (2012)
  40. 40. Global News, “Visualizing the split on Toronto City Council” (2012)
  41. 41. 5. Showing evolution of networks over time (clustering dynamics)
  42. 42. Global News, “Visualizing the split on Toronto City Council” (2012)
  43. 43. What we learned from story analysis and interviews: ! Seven common narrative functions: (1) Showing networks around an individual actor (ego-networks) (2) Revealing hubs or authorities (power law distributions) (3) Showing scale, complexity and topology of network (small worlds) (4) Showing paths or ties between nodes and the nature of these ties (strong and weak ties) (5) Showing alliances and oppositions (clustering) (6) Showing evolution of networks over time (7) Comparing networks
  44. 44. What we learned from story analysis and interviews: ! Good network stories take advantage of the properties of networks as media, in that the most common types of network narratives identified can be mapped back to key network properties or metrics. Stories that employ network concepts span a number of genres: investigations, special reports, explanatory and data journalism, etc. Themes that lend themselves to network analysis - largely associated with the object of investigative work: mapping money and political influence, power, corruption and organised crime networks. Actors tend to be elites, villains or victims (esp. in investigative journalism stories).
  45. 45. What we learned from story analysis and interviews: ! Network stories challenge some of the values of investigative journalism: the nature of the associations depicted through network analysis is often considered to be too elusive to be used as incriminating evidence in investigations. Network stories also challenge some of the values of news journalism such as recency, novelty and conflict: network stories do not necessarily tell something new or previously unknown, but rather organise existing information into patterns and structures; conflict and opposition are not immediately obvious from network structures. Sometimes closer to emerging epistemologies, e.g. those associated with the label data journalism (focus on structured data rather than stories)
  46. 46. So far: storytelling functions of networks in journalism. ! ! Next steps: ! ! What functions do forms of journalism based on networks as analytical and storytelling devices enact in society? ! What forms of civic engagement and action do they mobilise?
  47. 47. From ways in which statistics are used for social mobilisation (statactivism) to functions that journalism enacts in society through “network stories.”
  48. 48. Thank You! Liliana Bounegru | lilianabounegru.org | @bb_liliana

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