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Cinema Data Mining – The Smell of Fear 1 1 2 2 Jörg Wicker Nicolas Krauter Bettina Derstorff Christof Stönner 2 2 2 1 Efstratios Bourtsoukidis Thomas Klüpfel Jonathan Williams Stefan Kramer 2 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) 1 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