%0 Journal Article %J IEEE Access %D 2021 %T Improving the Fitness Function of an Evolutionary Suspense Generator Through Sentiment Analysis %A Delatorre, Pablo %A León, Carlos %A Salguero, Alberto %X The perception of suspense in stories is affected not only by general literary aspects like narrative structure and linguistic features, but also by anticipation and evocation of feelings like aversion, disgust or empathy. As such, it is possible to alter the feeling of suspense by modifying components of a story that convey these feelings to the audience. Based on a previous straightforward model of suspense adaptation, this paper describes the design, implementation and evaluation of a computational system that adapts narrative scenes for conveying a specific user-defined amount of suspense. The system is designed to address the impact of different types of emotional components on the reader. The relative weighted suspense of these components is computed with a regression model based on a sentiment analysis tool, and used as a fitness function in an evolutionary algorithm. This new function is able to identify the different weights on the prediction of suspense in aspects like outcome, decorative elements, or threat’s appearance. The results indicate that this approach represents a significant improvement over the previous existing approach. %B IEEE Access %V 9 %P 39626–39635 %8 03/2021 %G eng %U https://ieeexplore.ieee.org/abstract/document/9371672 %R https://doi.org/10.1109/ACCESS.2021.3064242 %0 Journal Article %J Knowledge-Based Systems %D 2020 %T Predicting the effects of suspenseful outcome for automatic storytelling %A Delatorre, Pablo %A León, Carlos %A Salguero, Alberto %A Tapscott, Alan %X Automatic story generation systems usually deliver suspense by including an adverse outcome in the narrative, in the assumption that the adversity will trigger a certain set of emotions that can be categorized as suspenseful. However, existing systems do not implement solutions relying on predictive models of the impact of the outcome on readers. A formulation of the emotional effects of the outcome would allow storytelling systems to perform a better measure of suspense and discriminate among potential outcomes based on the emotional impact. This paper reports on a computational model of the effect of different outcomes on the perceived suspense. A preliminary analysis to identify and evaluate the affective responses to a set of outcomes commonly used in suspense was carried out. Then, a study was run to quantify and compare suspense and affective responses evoked by the set of outcomes. Next, a predictive model relying on the analyzed data was computed, and an evolutionary algorithm for automatically choosing the best outcome was implemented. The system was tested against human subjects’ reported suspense and electromyography responses to the addition of the generated outcomes to narrative passages. The results show a high correlation between the predicted impact of the computed outcome and the reported suspense. %B Knowledge-Based Systems %V 209 %P 106450 %G eng %U https://www.sciencedirect.com/science/article/pii/S0950705120305797 %R https://doi.org/10.1016/j.knosys.2020.106450 %0 Journal Article %J Frontiers in Psychology %D 2019 %T The Impact of Context on Affective Norms: A Case of Study With Suspense %A Delatorre, Pablo %A Salguero, Alberto %A León, Carlos %A Tapscott, Alan %B Frontiers in Psychology %V 10 %P 1988 %G eng %U https://www.frontiersin.org/article/10.3389/fpsyg.2019.01988 %R 10.3389/fpsyg.2019.01988 %0 Journal Article %J Connection Science %D 2019 %T Information management in interactive and non-interactive suspenseful storytelling %A Delatorre, Pablo %A Carlos León %A Salguero, Alberto %A Palomo-Duarte, Manuel %A Pablo Gervás %B Connection Science %V 31 %P 82-101 %8 01/2019 %G eng %U https://www.tandfonline.com/doi/full/10.1080/09540091.2018.1454890 %9 Original Research %R 10.1080/09540091.2018.1454890 %0 Conference Paper %B {Proceedings of 5th AISB Symposium on Computational Creativity 2018} %D 2018 %T Outcome inference based on threat resources in suspenseful scenes %A Delatorre, Pablo %A León, Carlos %A Salguero, Alberto %A Palomo-Duarte, Manuel %A Pablo Gervás %B {Proceedings of 5th AISB Symposium on Computational Creativity 2018} %I Society with AI %C Liverpool (UK) %G eng %U http://aisb2018.csc.liv.ac.uk/PROCEEDINGS%20AISB2018/Computational%20Creativity%20-%20AISB2018.pdf %0 Conference Paper %B Proceedings of AISB Annual Convencion 2017 %D 2017 %T Impact of interactivity on information management for suspense in storytelling %A Delatorre, Pablo %A Carlos León %A Salguero, Alberto %A Mateo-Gil, Cristina %A Pablo Gervás %E Joanna Bryson, Marina De Vos, Julian Padget %B Proceedings of AISB Annual Convencion 2017 %I Society with AI %G eng %> http://nil.fdi.ucm.es/sites/default/files/Delatorre%202017%20-%20Interactivity%20and%20suspense_0.pdf %0 Conference Paper %B I. Rojas et al. (eds.): Advances in Computational Intelligence, 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, Cádiz, Spain, June 14-16, Proceedings, Part II, LNCS 10306 %D 2017 %T The Long Path of Frustration: a case of study with Dead by Daylight %A Delatorre, Pablo %A Carlos León %A Salguero, Alberto %A Mateo-Gil, Cristina %B I. Rojas et al. (eds.): Advances in Computational Intelligence, 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, Cádiz, Spain, June 14-16, Proceedings, Part II, LNCS 10306 %I Springer International Publishing %G eng %R doi: 10.1007/978-3-319-59147-6_57 %> http://nil.fdi.ucm.es/sites/default/files/Delatorre%202017%20-%20Long%20path%20of%20frustration_0.pdf %0 Conference Paper %B Proceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality %D 2016 %T Training to Capture Software Requirements by Role Playing %A Delatorre, Pablo %A Salguero, Alberto %B Proceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality %I ACM %C New York, NY, USA %@ 978-1-4503-4747-1 %G eng %U http://doi.acm.org/10.1145/3012430.3012611 %R 10.1145/3012430.3012611