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Interpretable Clusters for Representing Citizens’ Sense of Belonging through Interaction with Cultural Heritage

Articolo
Data di Pubblicazione:
2024
Abstract:
The EU H2020 project social cohesion, participation, and inclusion through cultural engagement (SPICE) focuses on developing, designing, and implementing new methods and digital tools for citizen curation. This article delineates several software tools developed within the project, presenting innovative approaches to represent and visualize citizens and communities resulting from their engagement with cultural heritage. Aligned with the central tenets of SPICE –particularly the notions of belonging and the interpretation reflection loop– the primary objective is to bolster citizens’ participation and inclusion in fostering social cohesion. This article describes how the SPICE tools can be utilized to guide the processes of interpretation and reflection on cultural heritage artifacts. The Community Model serves as a pivotal component, enabling the modeling of citizens and communities through the utilization of similarity functions for clustering citizens based on perspectives. The clustering algorithm is intricately crafted to generate coherent communities, iterating until all clusters are interpretable using demographic attributes, centroid-based representations, and similarity attributes. Authors posit that this model holds significant value in comprehending and structuring complex data within cultural heritage contexts. To exemplify our approach, the article examines different attributes of individual citizens and citizen groups in the Galleria Civica d’Arte Moderna e Contemporanea (GAM) case study. Here, perspectives are delineated based on visitors’ demographic attributes and their emotional responses when engaging with artworks. These perspectives are then visualized using the VISIR tool, facilitating the exploration and revelation of connections between citizens and communities, thereby bridging the realms of citizen space and cultural heritage space.
Tipologia CRIS:
03A-Articolo su Rivista
Keywords:
cultural heritage, citizen curation, artificial intelligence
Elenco autori:
Jiménez-Díaz, Guillermo; Diaz-Agudo, Belen; Emilio Bruni, Luis; Kadastik, Nele; Follo, Anna; Damiano, Rossana; Striani, Manuel; Sanchez-Martin, Angel; Lieto, Antonio
Autori di Ateneo:
DAMIANO Rossana
Link alla scheda completa:
https://iris.unito.it/handle/2318/2038294
Pubblicato in:
ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE
Journal
Progetto:
DAMIANO R. - Progetto UE H2020-RIA n. 870811 "SPICE" - Social Participation and Inclusion through Cultural Engagement
  • Dati Generali
  • Aree Di Ricerca

Dati Generali

URL

https://dl.acm.org/doi/10.1145/3665142

Aree Di Ricerca

Settori (14)


PE6_7 - Artificial intelligence, intelligent systems, natural language processing - (2024)

PE6_9 - Human computer interaction and interface, visualisation - (2024)

CIBO, AGRICOLTURA e ALLEVAMENTI - Farmacologia Veterinaria

CULTURA, ARTE e CREATIVITA' - Culture moderne

INFORMATICA, AUTOMAZIONE e INTELLIGENZA ARTIFICIALE - Digitalizzazione della Cultura e della Creatività

INFORMATICA, AUTOMAZIONE e INTELLIGENZA ARTIFICIALE - Digitalizzazione della Società e della Pubblica Amministrazione

INFORMATICA, AUTOMAZIONE e INTELLIGENZA ARTIFICIALE - Industria X.0

INFORMATICA, AUTOMAZIONE e INTELLIGENZA ARTIFICIALE - Salute e Informatica

LINGUE e LETTERATURA - Anglistica e angloamericanistica

LINGUE e LETTERATURA - Francesistica

PIANETA TERRA, AMBIENTE, CLIMA, ENERGIA e SOSTENIBILITA' - Diritto dell'Ambiente

PIANETA TERRA, AMBIENTE, CLIMA, ENERGIA e SOSTENIBILITA' - Informatica e Ambiente

SCIENZE MATEMATICHE, CHIMICHE, FISICHE - Fisica delle Particelle e dei Nuclei

SCIENZE MATEMATICHE, CHIMICHE, FISICHE - Laboratori innovativi, strumentazione e modellizzazione fisica
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