Learning Cognitive-Affective Digital Twins from Social Networks
comunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/159830
comunitat-uji-handle4:
INVESTIGACIONMetadatos
Título
Learning Cognitive-Affective Digital Twins from Social NetworksFecha de publicación
2021-10Editor
IOS PressISBN
9781643682105Tipo de documento
info:eu-repo/semantics/conferenceObjectVersión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
This paper presents an ongoing project about the implementation of digital twins (DT) for simulating cognitive-affective behaviours in social networks.
Our approach relies on a pure data-driven solution, which takes ... [+]
This paper presents an ongoing project about the implementation of digital twins (DT) for simulating cognitive-affective behaviours in social networks.
Our approach relies on a pure data-driven solution, which takes existing public data
from social networks to learn cognitive models according to the profile, posts and
interactions of the social network users. The final aim is that the learned cognitive models can be parameterised according to existing classifications of traits and
emotions so that different behaviours can be eventually simulated with the resulting DTs. In this work, we propose the use of the Transformers neural-network architectures to both interpret incoming messages according to cognitive contexts,
and to generate responses to these messages. The first experiments are aimed at
integrating and measuring existing approaches for emotion recognition from texts. [-]
Descripción
23rd International Conference of the Catalan Association for Artificial Intelligence, CCIA 2021Virtual.Lleida, in October 2021
Publicado en
Libro de actas: Artificial Intelligence Research and Development. Proceedings of the 23rd edition of the CCIA, held in Lleida, in October 2021Entidad financiadora
Ministry of Economy and Commerce | Universitat Jaume I
Código del proyecto o subvención
TIN2016-88835-RET | UJI-B2020-15
Derechos de acceso
info:eu-repo/semantics/openAccess