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Isase2018

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ISASE2018で発表したスライドです

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Isase2018

  1. 1. A Consideration to Estimate Spoiling Pages in Comics Yoshiki Maki Yuji Shiratori Kenta Sato Satoshi Nakamura Graduate School of Advanced Mathematical Sciences, Meiji University
  2. 2. Do you have experience to get disappointed by encountering the comic spoiler?
  3. 3. Have you read 〇〇○? Yes!!! I love Ms.△△ !!!Oh boy... Ms.△△ ? This is funny lol She is dead !!
  4. 4. Character A Character B
  5. 5. Oh NO!!! I got spoiler!!
  6. 6. Ms.△△ ? This is funny lol She is dead !! Conversation Tweet Websites Images We want to stop these Spoiler
  7. 7. Tweet Websites Images Ms.△△ ? This is funny lol She is dead !! Conversation Difficult to stop this spoiler
  8. 8. Ms.△△ ? This is funny lol She is dead !! Conversation Websites Images TweetThe Twitter Mute Button: A Web Filtering Challenge [Golbeck 12] Enable to block TV program spoilers on Twitter by making datasets Using this method, we can stop comic spoilers too
  9. 9. Ms.△△ ? This is funny lol She is dead !! Conversation Tweet ImagesWebsites Proposal of deleting plots from the reviews to the items with stories [Ikeda 10] Enable to block plot spoilers of story contents on review Using this method, we can stop comic spoilers too
  10. 10. Ms.△△ ? This is funny lol She is dead !! Conversation Tweet Websites Images No study to block image spoiler Focus on these spoiler
  11. 11. Stop images spoiler of comic contents Purpose
  12. 12. Related Work Story Spoilers Don’t Spoil Stories [Leavitt, 2011] In novel, Spoiler make more interesting Only clarify novel spoiler,not comic spoiler
  13. 13. Stop the images spoiler of comic contents Purpose Investigating the influence of comic spoiler Generate a pre-datasets of spoilers Make an pre-experiment whether the spoiler effect depending on spoiler timing or not
  14. 14. Generate Pre-Datasets
  15. 15. Generate Datasets Why “Generate datasets?” In related work, writer make a spoiler and we don’t think these spoiler is real spoiler. We want to select real spoiler but there are no study to clarify real spoiler. So we generate datasets by asking collaborators to select spoiler page Which page is the spoiler?
  16. 16. Datasets(Used Manga) Battle Sports Mystery Romance ©️Yoshihiro Tomigashi ©️Takeshi Obata ©️Tsujitomo ©️Taiyo Matsumoto ©️Tetsuya Tsutsu ©️Aki Shimizu ©️Sotara Akiduki ©️Toko Minami
  17. 17. Datasets(Design) a4 people who already read each comicParticipants Genre×2 Comic = 8 Comics Amount Manga Select and Rank(1st to 3rd) pages with spoilers Question
  18. 18. Datasets(Selected Scenes) Battle Sports Mystery Romance ©️Yoshihiro Tomigashi ©️Takeshi Obata ©️Tsujitomo ©️Taiyo Matsumoto ©️Tetsuya Tsutsu ©️Aki Shimizu ©️Sotara Akiduki ©️Toko Minami Dead or Alive Dead or Alive Win / Lose Ending Detect mystery Ending Confess love Confess love
  19. 19. Pre- Experiment
  20. 20. Pre-Experiment(Design) a120 people who not read each mangaParticipants 4 Genre×2 Comic = 8 Comics Amount Manga Enjoyment value Interest of the next episodeQuestion
  21. 21. Comics Story Comics Story Comics Story Questionnaire TimingSpoiler Timing Spoiled After Outline Spoiled After Part 1 Spoiled After Part 2 Comics StoryPart 1 Part 2 Part 3 Part 1 Part 2 Part 3 Part 1 Part 1 Part 2 Part 2 Part 3 Part 3 Outline Outline Outline Outline Experiment(Design) Without Spoiler
  22. 22. Questionnaire TimingSpoiler Timing Spoiled After Outline Without Spoiler Spoiled After Part 1 Spoiled After Part 2 Manga StoryPart 1 Part 2 Part 3 Part 1 Part 2 Part 3 Part 1 Part 1 Part 2 Part 2 Part 3 Part 3 Outline Outline Outline Outline Part 1 Part 2 Part 3 Part 2 Part 3 Part 3 Experiment(Design)
  23. 23. -0.5 0.0 0.5 1.0 1.5 2.0 Without Spoiler After Outline After Part.1 After Part.2 No significant difference Enjoyment Value at last in each group Enjoyment value is decreasing depending on timing
  24. 24. -0.5 0.0 0.5 1.0 1.5 2.0 Outline Spoiler Part 1 Spoiler Part 2 Spoiler Part 3 Pattern 0 Pattern 1 Pattern 2 Pattern 3 ● Spoiler Timing Translate Bar of Interest Of The Next Value Graph
  25. 25. -0.5 0.0 0.5 1.0 1.5 2.0 Outline Spoiler Part 1 Spoiler Part 2 Spoiler Part 3 Pattern 0 Pattern 1 Pattern 2 Pattern 3 ● Spoiler Timing Increasing at after outline group(10%) Decreasing at after Part2 group(5%) Translate Bar of Interest Of The Next Value Graph
  26. 26. The spoiler contents has a possibility to decrease readers purchase motivation Reading Last Part Immediately after spoiler Even if spoiling, enjoyment value is not changing If spoiling next episode, reader’s interest of next episode is decreasing Discussion Spoiler contents is bad contents!
  27. 27. The spoiler contents has a possibility to decrease readers purchase motivation Reading Last Part Immediately after spoiler Even if spoiling, enjoyment value is not changing If spoiling next episode, reader’s interest of next episode is decreasing Discussion
  28. 28. Immediately after spoiler If spoiling next episode, reader’s interest of next episode is decreasing Discussion Think and redefine “What contents is spoiler”
  29. 29. What is Spoiler? N+1 N+2NN-1 Redefinition about the spoiler The spoiler contents is the contents which reader get disappointed in episode N+1 if reader had read until episode N. N-2
  30. 30. Investigating the influence Of comic spoiler Stop the images spoiler of comic contents Find a characteristics of spoiler pages Making method of estimating spoiler Purpose SOLVED
  31. 31. Characteristics Of Spoilers
  32. 32. Characteristics Find A Special Features To create method of estimating spoiler images, we analysis spoiler pages in pre-datasets and find a special features in spoiler pages focus on frame size and words in spoiler pages. Words Frame
  33. 33. Characteristics(Selected Spoiler) Battle Sports Mystery Romans
  34. 34. Battle Frames Bigger frames than other pages Words “I won” and “Finished” Win/Lose words Characteristics(Several Genres)
  35. 35. Sports Frames Big frame and small frames Words Little words Characteristics(Several Genres)
  36. 36. Mystery Frame Bigger frame or smaller frames Words Many words or little words Characteristics(Several Genres)
  37. 37. Romans Frame Bigger size than other pages Words “I love you” Characteristics(Several Genres)
  38. 38. Characteristics(Selected Spoiler) Battle Sports Mystery Romans Collaborators can select only three pages in a comic Must make real spoiler datasets
  39. 39. Method Of Create Datasets
  40. 40. Method N+1 N+2NN-1 Question to the contributors Please select facing pages which you think that if you show the facing page in the story number N+1 to your friend who had read until the story number N, your friend will angry with you. N-2
  41. 41. Yellow Card Spoiler Rating: 0~49% Red Card Spoiler Rating: 50~100% Method Red card / yellow card Ask contributors to set two levels of spoiler to these pages.
  42. 42. How To Estimate Spoiler Pages
  43. 43. Estimate Spoiler Page Layout Analysis of Tree-Structured Scene Frames in Comic Images [Tanaka 2007] Vision API[Google 18] 1000~2000 Spoiler Pages Frame Word Page
  44. 44. Summary Pre-Experiment Stop the spoiler Generate a pre-datasets of spoilers Make an pre-experiment whether the spoiler effect depending on spoiler timing or not Find a characteristics of spoiler pages Making method of estimating spoiler
  45. 45. -0.5 0.0 0.5 1.0 1.5 2.0 Outline Spoiler1 Part.1 Spoiler2 Part.2 Spoiler3 Part.3 Without Spoiler With Spoiler1 With Spoiler2 With Spoiler3 ● Spoiler Timing Translate Bar of Enjoyment Value Graph
  46. 46. Translate Bar of Enjoyment Value Graph -0.5 0.0 0.5 1.0 1.5 2.0 Outline Spoiler1 Part.1 Spoiler2 Part.2 Spoiler3 Part.3 Without Spoiler With Spoiler1 With Spoiler2 With Spoiler3 ● Spoiler Timing Decreasing at after Part3 spoiler(10%)
  47. 47. OCR LI いい音だを ゼンに会って 1織にい る嚇で ーフん ヴつと 加舶加加鵬 JJI且1 い叫痢 し」 ONLINE OCR _鱒 慣のと 薔れ咆搬っ疋 泄ウに肩鱗う Tesseract 音だな うん オロ 知って しまった ゼンに会って 一緒にいる中で ずっと 途切れなかった ゼンに向かう 気持ちの 中に まだ M+ f 見つけていない 感情があった ゼン ゼンのことが 好きです SAS Vision API

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