A sensemaking system for grouping and suggesting stories from multiple affective viewpoints in museums

Abstract

ABSTRACTThis article presents an affective-based sensemaking system for grouping and suggesting stories created by the users about the cultural artefacts in a museum. By relying on the TCL commonsense reasoning framework, the system exploits the spatial structure of the Plutchik's "wheel of emotions" to organize the stories according to their extracted emotions. The process of emotion extraction, reasoning, and suggestion is triggered by an app, called GAMGame, and integrated with the sensemaking engine. Following the framework of Citizen Curation, the system allows classifying and suggesting stories encompassing cultural items able to evoke not only the very same emotions of already experienced or preferred museum objects but also novel items sharing different emotional stances and, therefore, able to break the filter bubble effect and open the users' view toward more inclusive and empathy-based interpretations of cultural content. The system has been designed tested, in the context of the H2020EU SPICE project (Social cohesion, Participation, and Inclusion through Cultural Engagement), in cooperation with the community of the d/Deaf and on the collection of the Gallery of Modern Art (GAM) in Turin. We describe the user-centered design process of the web app and of its components and we report the results concerning the effectiveness of the diversity-seeking, affective-driven, recommendations of stories.KEYWORDS: Story-based recommendationsdiversity-seeking emotional recommendationscommonsense reasoningaffective computingrecommender systems AcknowledgmentsThe research leading this publication has been partially funded by the European Union's Horizon 2020 research and innovation programme http://dx.doi.org/10.13039/501100007601 under grant agreement SPICE 870811. The publication reflects the author's views. The Research Executive Agency (REA) is not liable for any use that may be made of the information contained therein. We thank the GAM Museum and the Istituto dei Sordi di Torino for their help in setting up the evaluation.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 TCL is an acronym for Typicality-based Compositional Logic: the reasoning framework driving the behavior of the sensemaking system. The framework is described in Section 4.12 https://spice-h2020.eu/3 https://www.gamtorino.it/en4 http://conventions.coe.int/Treaty/EN/Treaties/Html/199.htm5 https://icom.museum/en/resources/standards-guidelines/museum-definition/6 DEGARI is an acronym that stands for Dynamic Emotion Generator and ReclassIfier.7 https://www.who.int/news-room/fact-sheets/detail/disability-and-health8 https://www.who.int/health-topics/disability9 https://access.si.edu/10 https://universaldesign.ie/What-is-Universal-Design/The-7-Principles/11 36 stories were created using Google Forms, but they are not included in the analysis due to the differences with the prototype.12 https://www.gamtorino.it/it/archivio-catalogo/estate-lamaca/13 https://www.gamtorino.it/it/archivio-catalogo/via-a-parigi/14 https://www.gamtorino.it/it/archivio-catalogo/le-tre-finestre-la-pianura-della-torre/15 https://reactjs.org/16 https://spice-h2020.eu/document/deliverable/D1.2.pdf17 The reasons leading to the choice of this model as grounding element of the DEGARI 2.0 system is twofold: on the one hand, this it is well-grounded in psychology and general enough to guarantee a wide coverage of emotions, thus giving the possibility of going beyond the emotional classification and recommendations in terms of the standard basic emotions suggested by models like the Ekman's one (widely used in computer vision and sentiment analysis tasks). This affective extension is aligned with the literature on the psychology of art suggesting that the encoding of complex emotions, such as Pride and Shame, could give further interesting results in AI emotion-based classification and recommendation systems (Silvia, Citation2009). Second, the Plutchik whee