TY - JOUR
T1 - A sensemaking system for grouping and suggesting stories from multiple affective viewpoints in museums
AU - Lieto, Antonio
AU - STRIANI, Manuel
AU - Gena, Cristina
AU - Dolza, Enrico
AU - Marras, Anna Maria
AU - Pozzato, Gian Luca
AU - Damiano, Rossana
N1 - Publisher Copyright:
© 2023 Taylor & Francis Group, LLC.
PY - 2024
Y1 - 2024
N2 - This 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.
AB - This 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.
KW - Story-based recommendations
KW - affective computing
KW - commonsense reasoning
KW - diversity-seeking emotional recommendations
KW - recommender systems
KW - Story-based recommendations
KW - affective computing
KW - commonsense reasoning
KW - diversity-seeking emotional recommendations
KW - recommender systems
UR - https://iris.uniupo.it/handle/11579/161123
U2 - 10.1080/07370024.2023.2242355
DO - 10.1080/07370024.2023.2242355
M3 - Article
SN - 2180-1347
VL - 39
SP - 109
EP - 143
JO - INTERNATIONAL JOURNAL OF HUMAN COMPUTER INTERACTION
JF - INTERNATIONAL JOURNAL OF HUMAN COMPUTER INTERACTION
IS - 1-2
ER -