2016
2.
Williams, Jonathan; Stönner, Christof; Wicker, Jörg; Krauter, Nicolas; Derstorff, Bettina; Bourtsoukidis, Efstratios; Klüpfel, Thomas; Kramer, Stefan
Cinema audiences reproducibly vary the chemical composition of air during films, by broadcasting scene specific emissions on breath Journal Article
In: Scientific Reports, vol. 6, 2016.
Abstract | Links | BibTeX | Altmetric | PlumX | Tags: atmospheric chemistry, causality, cheminformatics, data mining, emotional response analysis, smell of fear, sof, time series
@article{williams2015element,
title = {Cinema audiences reproducibly vary the chemical composition of air during films, by broadcasting scene specific emissions on breath},
author = {Jonathan Williams and Christof St\"{o}nner and J\"{o}rg Wicker and Nicolas Krauter and Bettina Derstorff and Efstratios Bourtsoukidis and Thomas Kl\"{u}pfel and Stefan Kramer},
url = {http://www.nature.com/articles/srep25464},
doi = {10.1038/srep25464},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
journal = {Scientific Reports},
volume = {6},
publisher = {Nature Publishing Group},
abstract = {Human beings continuously emit chemicals into the air by breath and through the skin. In order to determine whether these emissions vary predictably in response to audiovisual stimuli, we have continuously monitored carbon dioxide and over one hundred volatile organic compounds in a cinema. It was found that many airborne chemicals in cinema air varied distinctively and reproducibly with time for a particular film, even in different screenings to different audiences. Application of scene labels and advanced data mining methods revealed that specific film events, namely "suspense" or "comedy" caused audiences to change their emission of specific chemicals. These event-type synchronous, broadcasted human chemosignals open the possibility for objective and non-invasive assessment of a human group response to stimuli by continuous measurement of chemicals in air. Such methods can be applied to research fields such as psychology and biology, and be valuable to industries such as film making and advertising.},
keywords = {atmospheric chemistry, causality, cheminformatics, data mining, emotional response analysis, smell of fear, sof, time series},
pubstate = {published},
tppubtype = {article}
}
Human beings continuously emit chemicals into the air by breath and through the skin. In order to determine whether these emissions vary predictably in response to audiovisual stimuli, we have continuously monitored carbon dioxide and over one hundred volatile organic compounds in a cinema. It was found that many airborne chemicals in cinema air varied distinctively and reproducibly with time for a particular film, even in different screenings to different audiences. Application of scene labels and advanced data mining methods revealed that specific film events, namely "suspense" or "comedy" caused audiences to change their emission of specific chemicals. These event-type synchronous, broadcasted human chemosignals open the possibility for objective and non-invasive assessment of a human group response to stimuli by continuous measurement of chemicals in air. Such methods can be applied to research fields such as psychology and biology, and be valuable to industries such as film making and advertising.
2015
1.
Wicker, Jörg; Krauter, Nicolas; Derstorff, Bettina; Stönner, Christof; Bourtsoukidis, Efstratios; Klüpfel, Thomas; Williams, Jonathan; Kramer, Stefan
Cinema Data Mining: The Smell of Fear Proceedings Article
In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1235-1304, ACM ACM, New York, NY, USA, 2015, ISBN: 978-1-4503-3664-2.
Abstract | Links | BibTeX | Altmetric | PlumX | Tags: atmospheric chemistry, breath analysis, causality, cheminformatics, cinema data mining, data mining, emotional response analysis, movie analysis, smell of fear, sof, time series
@inproceedings{wicker2015cinema,
title = {Cinema Data Mining: The Smell of Fear},
author = {J\"{o}rg Wicker and Nicolas Krauter and Bettina Derstorff and Christof St\"{o}nner and Efstratios Bourtsoukidis and Thomas Kl\"{u}pfel and Jonathan Williams and Stefan Kramer},
url = {https://wicker.nz/nwp-acm/authorize.php?id=N10031
http://doi.acm.org/10.1145/2783258.2783404},
doi = {10.1145/2783258.2783404},
isbn = {978-1-4503-3664-2},
year = {2015},
date = {2015-01-01},
booktitle = {Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
pages = {1235-1304},
publisher = {ACM},
address = {New York, NY, USA},
organization = {ACM},
series = {KDD '15},
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 theatre over a whole month in intervals of thirty seconds, and annotated the screened films by a controlled vocabulary compiled from multiple sources. To gain a better understanding of the data and to reveal unknown relationships, we have built prediction models for so-called forward prediction (the prediction of future VOCs from the past), backward prediction (the prediction of past scene labels from future VOCs) and for some forms of abductive reasoning and Granger causality. Experimental results show that some VOCs and some labels can be predicted with relatively low error, and that hints for causality with low p-values can be detected in the data.},
keywords = {atmospheric chemistry, breath analysis, causality, cheminformatics, cinema data mining, data mining, emotional response analysis, movie analysis, smell of fear, sof, time series},
pubstate = {published},
tppubtype = {inproceedings}
}
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 theatre over a whole month in intervals of thirty seconds, and annotated the screened films by a controlled vocabulary compiled from multiple sources. To gain a better understanding of the data and to reveal unknown relationships, we have built prediction models for so-called forward prediction (the prediction of future VOCs from the past), backward prediction (the prediction of past scene labels from future VOCs) and for some forms of abductive reasoning and Granger causality. Experimental results show that some VOCs and some labels can be predicted with relatively low error, and that hints for causality with low p-values can be detected in the data.