Hi everyone I'm Xingyu Lan from Tongji University
Today I'll be presenting our work: Understanding Narrative Linearity for Telling Expressive Time-Oriented Stories
This paper was co-authored by Xingyu Lan, Xinyue Xu, and Nan Cao from Intelligent Big Data Visualization Lab, Tongji University
Creating expressive narrative visualization often requires choosing a well-planned narrative order
According to narratologist Gérard Genette, every story has two orders:
the natural order of the story which is always chronological
and the order in which it is narrated
so when narrating a story
the narrative can either follow the linear order of the story events which is chronology
or deviate from linearity which are also called anachronies
for example in this story
when presenting the social progress of Sweden
Hans Rosling starts from 2004,
then flashbacks to 1709
and then tells chronologically until 2004 again
while evidence exists that anachronies can enhance story expressiveness in novels and films
how they can 18 0:01:30.592,0:01:36.567 19 type of narrative visualization 20 that is time-oriented stories 21 so basically time-oriented stories are stories that based on temporal data
such as the history or the progression of certain things
we then ask two specific research questions:
first, what are the regular patterns of 25 0:02:01.367,0:02:08.672 26 order patterns help improve story expressiveness? 27 to address these questions --> 28 first --> we conducted preliminary interviews with seven experts 29 we identified six motivations and two challenges 30 of manipulating narrative linearity in time-oriented stories 31 for example --> we found that 32 balancing the expressiveness and the comprehensibility of a story is challenging 33 then --> we analyzed a corpus of 80 time oriented stories
and identified six most salient patterns of narrative orders
including chronology and five 36 0:02:47.760,0:02:51.406 37 0:02:51.406,0:02:55.754 38 0:02:55.834,0:02:58.155 39 0:02:58.155,0:03:01.952 40 0:03:02.080,0:03:07.040 41 0:03:07.040,0:03:09.644 42 0:03:10.014,0:03:13.270 43 0:03:15.120,0:03:20.376 44 0:03:20.376,0:03:23.742 45 0:03:23.742,0:03:25.903 46 0:03:25.903,0:03:29.179 47 0:03:29.179,0:03:34.480 48 0:03:34.480,0:03:37.831 49 0:03:37.831,0:03:42.000 50 0:03:42.320,0:03:45.495 51 0:03:45.495,0:03:51.000 52 0:03:51.000,0:03:55.402 53 they were assigned to 54 and here are the results 55 first --> we did not find significant difference in recall between chronology and anachronies 56 or between the six patterns 57 second --> we found that anachronies performed better than chronology
in some user engagement metrics
such as focused 60 0:04:18.482,0:04:24.246 61 0:04:24.246,0:04:28.714 62 0:04:28.847,0:04:33.457 63 0:04:33.457,0:04:37.818 64 0:04:38.480,0:04:42.823 65 0:04:42.823,0:04:47.479 66 0:04:47.479,0:04:50.706 67 0:04:50.706,0:04:55.989 68 0:04:55.989,0:04:58.633 69 0:04:58.633,0:05:00.072 70