Download Cinema Data Mining – The Smell of Fear

Cinema Data Mining – The Smell of Fear
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Jörg Wicker
Nicolas Krauter
Bettina Derstorff
Christof Stönner
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Efstratios Bourtsoukidis
Thomas Klüpfel
Jonathan Williams
Stefan Kramer
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Johannes Gutenberg University Mainz
Max-Planck-Institute for Chemistry
Abstract
While the physiological response of humans to emotional events or stimuli is well-investigated for many modalities (like EEG, skin resistance, . . . ), surprisingly little is known about the exhalation
of so-called Volatile Organic Compounds (VOCs) at quite low concentrations in response to such stimuli. VOCs are molecules of relatively small mass that quickly evaporate or sublimate and can
be detected in the air that surrounds us. The paper introduces a new field of application for data mining, where trace gas responses of people reacting on-line to films shown in cinemas (or movie
theaters) are related to the semantic content of the films themselves. To do so, we measured the VOCs from a movie theater over a whole month in intervals of thirty seconds, and annotated the
screened films by a controlled vocabulary compiled from multiple sources. The data set is publicly available at: https://github.com/joergwicker/smelloffear.
Emotional Response Analysis
Scene Annotations
I Human emotional response analysis well studied on many modalities
(EEG, skin resistance,...)
I Little known about exhalation of Volatile Organic Compounds (VOCs)
in relation to emotional response
. Do we communicate via exhaling VOCs?
. Which VOCs do we exhale given certain emotional stimuli?
Cinema
Screening Room
Ventilation
System
air flow
I 15 movies in 104 screenings
I 6 movies selected for analysis
I But: No standard scene
annotations available
. Use combination of previously
used labels and movie genres
I Shots per second
I SAM – Self Assessment
Manikin
I 63 screenings (46 of them
usable)
air flow
air flow
Analysis
Causality
forward-backward
romance
Acetone
Outside
Mass
Spectrometry
target
action
backward /
Isoprene
7
ROC Curve
abductive
reasoning
...
VOCs Data – CO2
Acetone
target
CO2
7
...
Isoprene
7
7
3,500
3,000
ROC Curve
2,500
CO2 (ppm)
3
ROC Curve
forward
...
3
2,000
t = -00:30
...
t = -05:00
1,500
1,000
t=0
t = +00:30
...
t = +05:00
ROC Curve
...
forward-backward
500
2013-12-18
2013-12-23
2013-12-28
2014-01-02
2014-01-07
2014-01-12
Time
1,300
Results and Conclusion
1,000
1,200
1,100
900
CO2 (ppm)
CO2 (ppm)
1,000
900
800
700
600
800
700
600
500
500
400
300
00:00
04:00
08:00
12:00
16:00
20:00
00:00
400
12:30
13:15
1,600
1,400
14:00
14:45
15:30
16:15
Time – 2014-12-26 – Hunger Games
Time – 2014-12-26
CO2 concentration (ppm)
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12/26
12/27
12/28
12/29
1,200
1,000
17:00
I 30% holdout, leave-one-movie-out
I Several findings, for example
. blood (violence) – Ammonia
. blood (violence) – Acetone
. comedy – Formaldehyde
I New experiments with more
annotators
. suspense – Isoprene
. romance – Isoprene
. injury – Siloxanes
I Currently identifying molecules
I Unique combination
. Atmospheric Chemistry
. Breath analysis
. Emotional response
analysis
. Movie analysis
. Data Mining
I New measurements done in
02/15
I New measurements planned
for 12/15
800
Data Set
600
400
12:45
13:15
13:45
14:15
14:45
15:15
15:45
16:15
Time – Hunger Games
[email protected]
16:45
Data set is available at GitHub:
https://github.com/joergwicker/smelloffear
https://github.com/joergwicker/smelloffear