ENTER 2015 Research Track Slide Number 1

Spatiotemporal Analysis of Rambling Activities:

Approach to Inferring Visitor Satisfaction

Masakatsu Ohtaa

Yuta Watanabeb

Toshiaki Miyazakib

aNTT Network Innovation Laboratories,

NTT Corporation, Japan

bSchool of Computer Science and Engineering,

The University of Aizu, Japan

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Challenge

which?

trajectory of trip

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Agenda

1. Introduction

2. Approach– Spatiotemporal analysis

1. Case Study– Campus festival

1. Conclusions

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Planning with ICT

• Make practical plans under time & budget constraints

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Rambling Activities

stop by

stop by

original

• Trajectory deviates from efficient route

actual

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Encounter the Unexpected

what?Interesting!

bicycle?

clog?

man?

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Independent Choiceswhere to go next?

after determining

vs.

Expectation increasescontent about

choice

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Rambling Activities and Visitor Satisfaction

• Rambling activities meet following conditions:– Encounter the unexpected– Independent Choices

Person rambling in area is likely attracted to it

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Sustainable Development

inducerambling

urban plannersevent organizers …

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Goal• Contributes to check phase

‒ Visitors were rambling in area?‒ Area is attractive to them?

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Agenda

1. Introduction

2. Approach– Spatiotemporal analysis

1. Case Study– Campus festival

1. Conclusions

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Prominent Attributes

• Spatiotemporal Dispersal of Visits– Many visited spots– Various dwell times at various spots

• Unplanned “Stopping by”– Not efficient route– Many intersections in trajectory

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Spatiotemporal Analysis

3D curve: locations of visited spotsxyz dwell times at visited spots

more rambling

Y

X

Z

Y

X

Z

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Knot Theory

unknot 3.1 4.1 5.1 5.2

6.1 6.2 6.3 7.1 7.2

7.3 7.4 7.5 7.6 7.7

distinct knots (examples)

equivalent knots

unknot

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Creating Knot

3D curve3D curve

ClosingClosing

SimplificationSimplification

start end

dwell time

trajectory

deform to equivalent knots

3D curve

springspring

start

beadbead

spot spot

spot end

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ExamplesDispersal & Unplanned Dispersal & Unplanned

Spatially biasedSpatially biased

Temporally biasedTemporally biased

Well scheduledWell scheduled

simplify

knot

unknot

unknot

unknotdwell time length

transform

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Determination of Rambling

knot

unknotdwell time length

transformRambling

NOT Rambling

trajectory

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Agenda

1. Introduction

2. Approach– Spatiotemporal analysis

1. Case Study– Campus festival

1. Conclusions

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Campus Festival

Similar to towns• Open to public• Various spots and events

food stands, concerts, lectures…

Restricted space• Controlled experiment• Many trajectories at a time

Date: Oct. 12th and 13th, 2013Location: The University of Aizu Visitors: 5,200

Date: Oct. 12th and 13th, 2013Location: The University of Aizu Visitors: 5,200

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Experiment Design

Indoor

Outdoor

100 mbeacon reader( spot )

beacon venue

Date: Oct. 13th, 2013Number of spots: 21Participants: 135 groupsRegular visitors: 77%

Date: Oct. 13th, 2013Number of spots: 21Participants: 135 groupsRegular visitors: 77%

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Evaluations

1. Inferring visitor satisfaction– Were participants who rambled

satisfied?

1. Regular and non-regular difference– Did non-regular visitors go around

venue much more?

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Satisfaction Measure

• Difficult to understand visitor’s true impressions• New measure:

• If overspending > 1.25:

more satisfied than expected

from 0.75 to 1.25: stayed on scheduled(estimated error in planning: 0.25)

overspending = actual spending time

planned spending time

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1) Visitor Satisfaction

• Significant differences (Fisher’s Exact Test: p=0.008)

• Finding‒ Detecting rambling activities‒ Inferring visitor satisfaction

• Significant differences (Fisher’s Exact Test: p=0.008)

• Finding‒ Detecting rambling activities‒ Inferring visitor satisfaction

more satisfied with festival than originally expected

more satisfied with festival than originally expected

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2) Regular and non-Regular Visitors

• NO significant differences (Fisher’s Exact Test: p=0.51)

• Finding‒ Influence of Social Validation:

Imitate others’ opinions and behaviors

• NO significant differences (Fisher’s Exact Test: p=0.51)

• Finding‒ Influence of Social Validation:

Imitate others’ opinions and behaviors

*regular visitors: 77%

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Conclusions

• Detected trajectories caused by rambling activities• Inferred visitor satisfaction

Future work:Compare rambling activities between different environments

City A City B

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references

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Spot 1Spot 1 Spot 2Spot 2 Spot 3Spot 3 Spot 4Spot 4 Spot 5Spot 5

Adjusted Dwell Time

real dwell time

adjusted dwell time

order of length

10 120 1030 60

1 4 12 3

1L 4L 1L2L 3L

trajectory

• Emphasize variation in length of dwell time

*L: parameter

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Conventional Method

overspending time rateoverspending time rate

Difficult to infer participant satisfaction by “trajectory length” and “spending-time at venue”

more satisfied with festival than originally expected