TY - GEN
T1 - Second International Workshop on Recommender Systems for Sustainability and Social Good (RecSoGood 2025)
AU - Boratto, Ludovico
AU - De Filippo, Allegra
AU - Lex, Elisabeth
AU - Malloci, Francesca Maridina
AU - Mauro, Noemi
AU - Ricci, Francesco
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s).
PY - 2025/9/7
Y1 - 2025/9/7
N2 - In the rapidly evolving landscape of technology and sustainability, leveraging Recommender Systems has emerged as a powerful tool for driving positive change. With a foundation in AI and data analytics, Recommender Systems can be effective in various domains, from e-commerce to energy management, inclusion and well-being. By harnessing the power of recommendation algorithms under a multi-stakeholder perspective, organizations and researchers can guide users towards more sustainable choices and behaviors, contributing to broader environmental and social goals. With this aim, our workshop provides a unique platform for researchers, practitioners, and platform owners to explore the integration of sustainability principles into Recommender Systems. Through presentations, discussions, and panels, participants can explore the theoretical foundations, practical implementations, and ethical and environmental considerations of sustainable Recommender Systems. By fostering collaboration and knowledge exchange, the workshop aims to catalyze innovation and inspire collective action towards a more sustainable future.
AB - In the rapidly evolving landscape of technology and sustainability, leveraging Recommender Systems has emerged as a powerful tool for driving positive change. With a foundation in AI and data analytics, Recommender Systems can be effective in various domains, from e-commerce to energy management, inclusion and well-being. By harnessing the power of recommendation algorithms under a multi-stakeholder perspective, organizations and researchers can guide users towards more sustainable choices and behaviors, contributing to broader environmental and social goals. With this aim, our workshop provides a unique platform for researchers, practitioners, and platform owners to explore the integration of sustainability principles into Recommender Systems. Through presentations, discussions, and panels, participants can explore the theoretical foundations, practical implementations, and ethical and environmental considerations of sustainable Recommender Systems. By fostering collaboration and knowledge exchange, the workshop aims to catalyze innovation and inspire collective action towards a more sustainable future.
KW - Behavioural Change
KW - Recommendation
KW - Social Good
KW - Sustainability
KW - Sustainable Development Goals
UR - https://www.scopus.com/pages/publications/105019641621
U2 - 10.1145/3705328.3748497
DO - 10.1145/3705328.3748497
M3 - Conference paper
AN - SCOPUS:105019641621
T3 - RecSys2025 - Proceedings of the 19th ACM Conference on Recommender Systems
SP - 1394
EP - 1398
BT - RecSys2025 - Proceedings of the 19th ACM Conference on Recommender Systems
PB - Association for Computing Machinery (ACM)
T2 - 19th ACM Conference on Recommender Systems, RecSys 2025
Y2 - 22 September 2025 through 26 September 2025
ER -