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Metaphors in Qualitative Research & Synthesis

Originally delivered at UI21 in Boston in 2016, a talk on how to elicit apt metaphors from research participants and from a research team in the process of synthesis, for greater understanding.

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Metaphors in Qualitative Research & Synthesis

  1. 1. Metaphors in Qualitative Research & Synthesis Photo: Jurgen Wagner on Wikimedia Commons under CC-SA
  2. 2. “It’s crazy. It’s creepy even. It’s like I agreed to coffee with this company and then suddenly they’re proposing marriage.”
  3. 3. It’s crazy. It’s creepy even. It makes me uncomfortable.
  4. 4. [crying] “I’m sorry, I’m so upset.” Me: “Take your time...can you say what happened?” “I was about to see my great-great grandmother, and then it was just like this wall in my face. Like I smashed into a wall. I’m sorry.”
  5. 5. I was about to see my great-great grandmother, and then I was blocked. It was hugely frustrating. RIP
  6. 6. The original brief: “We’re seeing lots of abandons at the paywall. We want you to figure out what’s going on so we can tweak it. RIP
  7. 7. wall
  8. 8. Metaphor: a figure of speech which makes an implicit, implied, or hidden comparison between two things that are unrelated but share some common characteristics Dead Metaphor: a figure of speech which has lost the original imagery of its meaning due to extensive, repetitive, and popular usage
  9. 9. “The essence of metaphor is understanding and experiencing one kind of thing in terms of another.” - George Lakoff, Metaphors We Live By
  10. 10. for
  11. 11. Photo: NASA/JPL-CalTech
  12. 12. User Journey Anyone? RIP
  13. 13. User Journey User QUEST User TRIP User COMMUTE
  14. 14. This is just an errand for me. I don’t need a steed and a herald.
  15. 15. Qualitative datasets are full of metaphors.
  16. 16. Most qualitative data is word-based. Things participants said. Notes our team made. It comes in huge volumes. How do we make sense of it? Field Notes
  17. 17. Clustering & discussion Photo: Jurgen Wagner on Wikimedia Commons under CC-SA
  18. 18. The tools we reach for most 37% Failure rate Conversion rate Analytics
  19. 19. Finding the metaphors and systems of metaphors shows us the colorful, human side of the data and allows us to focus our number and picture work.
  20. 20. System 1 and System 2 The fast, subconscious side of our brains makes new associations with existing patterns. The slow, deliberative side checks associations and thinks logically abstractly. Participants make metaphors, and we interpret them, with System 1.
  21. 21. “Let seed be grass and grass turn into hay - I’m martyr to a motion not my own. What’s freedom for? To know eternity. I swear she cast a shadow white as stone.” - Theodore Roethke, I knew a woman
  22. 22. “I swear she cast a shadow white as stone.” The presence of the lovely woman is a variable that correlates with significant changes in the poet’s perceptions along all four dimensions. Substantial Black Sane Sworn Ethereal White Raving Flip
  23. 23. Paying attention to a user’s subconscious associations (metaphors) gives us richer information to consciously interpret and use in our designs.
  24. 24. 45 interviews 75 minutes each
  25. 25. People kept mentioning the word gem when talking about their interactions with news.
  26. 26. Gems are precious.
  27. 27. Gems are Hoarded Displayed Given as gifts
  28. 28. Back to the data: sure enough. People were hoarding, gifting, and displaying interesting bits of news.
  29. 29. NOPE Yep yep yep It’s a messy process.
  30. 30. 5 whys ways If people talk about something five different ways, it’s virtually certain at least one of them will be an apt metaphor.
  31. 31. coffee marriage
  32. 32. Can you say that another way?
  33. 33. Miller’s Law “In order to understand what another person is saying, you must assume that it is true, and try to imagine what it could be true of.”
  34. 34. OK but how?
  35. 35. There is often some unpoetic work in surfacing the metaphors.
  36. 36. Grounded Theory Social scientists use a multi-step process to code research transcripts. First, meticulously identify the interesting phrases. Then, keep notes on your theories about the importance of your highlights. Connect those notes into solid analysis.
  37. 37. Look for metaphors and metaphor-ish analogies that spark your interest. Don’t forget the dead ones. RIP
  38. 38. Metaphors to look for
  39. 39. Love, Sex, & Friendship What kind of attraction does a participant have to what you’re researching?
  40. 40. Food & Shelter What kind of meal, or house, equates to their wishes?
  41. 41. Status & Competition What kind of contest are they trying to win?
  42. 42. Places Where could the experience they’re describing be ordinary?
  43. 43. Animals What creature shows similar behavior?
  44. 44. Our friends the spreadsheets
  45. 45. =countif(B2:G101, "wall")
  46. 46. Bolder can be easier ➔ Victory over winning over competitive advantage ➔ Madness over rule-bending ➔ Journey over trip BUT it still has to work when you bring it back down.
  47. 47. How do you tell if it fits?
  48. 48. When metaphors don’t work RIPDiagram: Charles Fadel on Wikimedia Commons under CC-SA
  49. 49. Two adventures
  50. 50. CHOCO Nothing was as it seemed Everything was as he promised
  51. 51. If you’re going to lead people on an adventure into metaphor, announce it and let them know what to expect (as far as you can). Be real and keep your promises.
  52. 52. Invite your team ➔ Show them what you’re doing ➔ Make the rules clear ➔ Send them home with gifts We need more people working in the world of color.
  53. 53. Work boldly in the world of color and connection
  54. 54. Thank you so much for listening! @cydharrell any time you want to talk about this