iPad Companion Apps for TV Shows

Companion Apps for Long Arc TV Series: 
Supporting New Viewers in Complex Storyworlds with Tightly Synchronized Context-Sensitive Annotations

This is the presentation for the recent research publication available at:
http://dl.acm.org/citation.cfm?id=2602299.2602317

Official Page: http://etv.gatech.edu/storymap/

Design Process: http://abhishek.im/projects/story-map/

Transcript

1. Companion Apps for Long Arc TV Series 
 Supporting New Viewers in Complex Storyworlds with Tightly Synchronized Context-Sensitive Annotations 
 Abhishek Nandakumar, Janet Murray
2. Digital affordances have allowed television to adopt complex + transmedia story telling.
3. More characters, longer story arcs. Viewers expect greater consistency.
4. TV via Internet: Binge Viewing by the Season
5. 40 characters/episode
6. Previously on… SECONDS 2 0 Retrospective montages 1 2 UPTO Individual Scene Excerpts SECONDS BETWEEN 3 0 How do we keep up?
7. Distractions: Social Apps, Trivia, Polls SHOWTIME SHO SYNC INTO NOW
8. HBOGo: Synchronous Non-Contextual
9. Writer’s Room: Overwhelmed
10. TV COMPANION APPS + Rich field for design Clear readiness for use
11. Our Survey 98 Participants Male 63% 37% Female 17-30 31-40 41-60 60+ 0 0.125 0.25 0.375 0.5 4% 23% 27% 45% Age Distribution
12. Our Survey 81% used second screen while watching TV 86% looked up information about shows they watch
13. TV show related Unrelated Communication Unrelated Consumption Social Media Gaming Only Watch TV Other 4% 5% 8% 20% 22% 16% 25% How do they use second screens? Our Survey
14. Characters/Relations Plot Location/Events Products Trivia Other 11% 14% 9% 16% 23% 27% What do they lookup online? …of 86% seeking info about shows
16. Character Map
17. Annotations: Synchronized and On-Demand
18. Video Annotations and Montages
19. Relationships
20. HTTP Requests playPause(video) Timecode HTTP Requests SyncCode current(scene) System Components for Syncing MySQL Database
21. Iterative Design Tested episode 11 (of 13), not discrete scenes Changed relationships as show progressed (no spoilers) Distinguished Newbies’ needs from Returning Viewers’ Added richer context-sensitive information for characters and plot references Added 3 minute montages to introduce each character
22. Tested comprehension against control group 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 without iPad with iPad Questions Characters Relations
23. Preliminary Usability Study Participants expected to use it less continuously at home than in test situation and therefore less distracting 5.2/10 on “helpful” 7 of the 8 used words like “very helpful” and “extremely helpful” to describe it Most useful features: Synchronized relationships display and event montages. 3.1/10 on “distracting”
24. “Helpful” Features Text Annotations Character bios Event descriptions Dialog Allusions clarified Key Event Montages “ABC doesn’t explain anything, HBO does…but you have to keep searching…” and “…you can even see characters change through the season”.
25. Scene-level Context for character map, annotations “Helpful” Features Complete Character Map “visual overview tells me who plays a bigger role…whom to pay attention to”.
26. Design Issue Length of montages 48 seconds longest paused interaction 10-15-30-45 secs worth investigating On-demand after show: 3 mins may be appropriate
27. Design Issue To pause or not to pause? New and veteran viewers watching together Automatic or manual? (perhaps a user setting) Separately from video – Sync by listening? Lack of pause – Bookmark to view later?
28. Tentative Guidelines Companion App Design Opt-in to enable automatically pause Context-sensitive info, deep dive on demand Social context of shared viewing: Present text or silent/ subtitled montages or bookmarks Emphasis on character relationships Summaries: Key past events
29. Design Issue Need for Authoring Systems
30. Future Work Open Research Questions Capturing + supporting mental models of an unfolding story Other forms: Documentaries, reality shows, sports, news Visual standards for efficient communication of relationships Supporting narrative immersion + empathy for characters
31. Thanks to the eTV team 2012-2013 Sergio Goldenberg Kartik Agarwal Tarun Chakravorty Jonathan Cutrell Abraham Doris-Down Harish Kothandaraman Michelle Linder Zuiena Kabir Bala Ganapathi Projects (past and present): http://etv.gatech.edu/
32. Fin. @JanetMurray @xAbhishek