WeNet
WeNet

WeNet
WeNet
 : 
The Internet of Us
The Internet of Us

A Project coordinated by IIIA.

Web page:

Principal investigator: 

Collaborating organisations:

University of Trento (Italy)
Idiap Research Institute (Switzerland)
Open University of Cyprus (Cyprus)
Ben-Gurion University of the Negev (Israel)
U-Hopper (Italy)
London School of Economics and Political Science (...

[see more]

University of Trento (Italy)
Idiap Research Institute (Switzerland)
Open University of Cyprus (Cyprus)
Ben-Gurion University of the Negev (Israel)
U-Hopper (Italy)
London School of Economics and Political Science (United Kingdom)
Eberhard Karls University of Tübingen (Germany)
Aalborg University (Denmark)
Martel GMBH (Switzerland)
Universidad Católica Nuestra Señora de la Asunción (Paraguay)
National University of Mongolia (Mongolia)
Amrita Vishwa Vidyapeetham (India)
Instituto Potosino de Investigación Científica y Tecnológica (Mexico)
Jilin University (China)

Funding entity:

European Commission
European Commission

Funding call:

H2020-FETPROACT-2018-01
H2020-FETPROACT-2018-01

Funding call URL:

Project #:

823783
823783

Total funding amount:

6.587.158,00€
6.587.158,00€

IIIA funding amount:

601.278,00€
601.278,00€

Duration:

01/Jan/2019
01/Jan/2019
31/Dec/2022
31/Dec/2022

Extension date:

Diversity permeates our everyday life and covers many dimensions, such as competence, culture, gender or economic across humans and social relations. Technology has evolved to a point where humans from diverse backgrounds, cultures, and experiences have an unprecedented ability to connect with each other. Yet technology does not in-and-by-itself provide support for developing and maintaining the social relationships that transcend geographical and cultural backgrounds. WeNet addresses this gap by providing a diversity-aware, machine-mediated paradigm of social relations. The goal is connecting people that can support each other, and the key is leveraging their diversity. The WeNet paradigm includes a family of computational diversity-aware models supporting human interaction. Learning models construct diversity profiles based on people's past behaviour and interactions. A diversity-aware search builds upon these profiles to connect the "right" people together. To support people’s interactions, a diversity alignment mechanism lifts communication barriers to ensure that messages between humans are interpreted correctly, and a diversity-aware incentive mechanism generates incentives to motivate people to support each other. The entire paradigm is developed taking into consideration ethical guidelines. The WeNet platform provides the technological infrastructure to set out a series of studies that will be carried within universities worldwide with diverse student populations, and with the final goal of improving students' quality of life inside and outside the academic environment. Beyond universities, WeNet's innovative paradigm impacts human interactions in general, especially those that may benefit from a collaborative approach (creative industries, medical diagnosis, ...). The WeNet consortium will develop a research infrastructure that will allow the exploitation of the project results and strengthen the European innovation eco-system in a worldwide perspective.

Diversity permeates our everyday life and covers many dimensions, such as competence, culture, gender or economic across humans and social relations. Technology has evolved to a point where humans from diverse backgrounds, cultures, and experiences have an unprecedented ability to connect with each other. Yet technology does not in-and-by-itself provide support for developing and maintaining the social relationships that transcend geographical and cultural backgrounds. WeNet addresses this gap by providing a diversity-aware, machine-mediated paradigm of social relations. The goal is connecting people that can support each other, and the key is leveraging their diversity. The WeNet paradigm includes a family of computational diversity-aware models supporting human interaction. Learning models construct diversity profiles based on people's past behaviour and interactions. A diversity-aware search builds upon these profiles to connect the "right" people together. To support people’s interactions, a diversity alignment mechanism lifts communication barriers to ensure that messages between humans are interpreted correctly, and a diversity-aware incentive mechanism generates incentives to motivate people to support each other. The entire paradigm is developed taking into consideration ethical guidelines. The WeNet platform provides the technological infrastructure to set out a series of studies that will be carried within universities worldwide with diverse student populations, and with the final goal of improving students' quality of life inside and outside the academic environment. Beyond universities, WeNet's innovative paradigm impacts human interactions in general, especially those that may benefit from a collaborative approach (creative industries, medical diagnosis, ...). The WeNet consortium will develop a research infrastructure that will allow the exploitation of the project results and strengthen the European innovation eco-system in a worldwide perspective.

In Press
Nardine Osman,  Ronald Chenu-Abente,  Qiang Shen,  Carles Sierra,  & Fausto Giunchiglia (In Press). Empowering Users in Online Open Communities. SN Computer Science. [BibTeX]  [PDF]
2024
Thiago Freitas Santos,  Nardine Osman,  & Marco Schorlemmer (2024). Can Interpretability Layouts Influence Human Perception of Offensive Sentences?. Davide Calvaresi, Amro Najjar, Andrea Omicini, Reyhan Aydogan, Rachele Carli, Giovanni Ciatto, Joris Hulstijn, & Kary Främling (Eds.), Explainable and Transparent AI and Multi-Agent Systems - 6th International Workshop, EXTRAAMAS 2024, Auckland, New Zealand, May 6-10, 2024, Revised Selected Papers (pp. 39--57). Springer. https://doi.org/10.1007/978-3-031-70074-3_3. [BibTeX]
Thiago Freitas Santos,  Nardine Osman,  & Marco Schorlemmer (2024). Is This a Violation? Learning and Understanding Norm Violations in Online Communities. Artificial Intelligence, 327. https://doi.org/10.1016/j.artint.2023.104058. [BibTeX]
2023
Thiago Freitas Santos,  Nardine Osman,  & Marco Schorlemmer (2023). A multi-scenario approach to continuously learn and understand norm violations. Autonomous Agents and Multi-Agent Systems, 37, 38. https://doi.org/10.1007/s10458-023-09619-4. [BibTeX]
Dimitra Bourou,  Marco Schorlemmer,  & Enric Plaza (2023). An Image-Schematic Analysis of Hasse and Euler Diagrams. Maria M. Hedblom, & Oliver Kutz (Eds.), Proceedings of The Seventh Image Schema Day co-located with The 20th International Conference on Principles of Knowledge Representation and Reasoning (KR 2023), Rhodes, Greece, September 2nd, 2023 . CEUR-WS.org. https://ceur-ws.org/Vol-3511/paper\_05.pdf. [BibTeX]
Thiago Freitas Santos,  Stephen Cranefield,  Bastin Tony Roy Savarimuthu,  Nardine Osman,  & Marco Schorlemmer (2023). Cross-community Adapter Learning {(CAL)}to Understand the Evolving Meanings of Norm Violation. Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, {IJCAI}2023, 19th-25th August 2023, Macao, SAR, China (pp. 109--117). ijcai.org. https://doi.org/10.24963/IJCAI.2023/13. [BibTeX]
2022
Nieves Montes,  Nardine Osman,  & Carles Sierra (2022). Combining Theory of~Mind and~Abduction for~Cooperation Under Imperfect Information. Multi-Agent Systems (pp 294--311). Springer International Publishing. https://doi.org/10.1007/978-3-031-20614-6_17. [BibTeX]  [PDF]
Thiago Freitas Dos Santos,  Nardine Osman,  & Marco Schorlemmer (2022). Ensemble and Incremental Learning for Norm Violation Detection. Piotr Faliszewski, Viviana Mascardi, Catherine Pelachaud, & Matthew E. Taylor (Eds.), 21st International Conference on Autonomous Agents and Multiagent Systems, {AAMAS}2022, Auckland, New Zealand, May 9-13, 2022 (pp. 427--435). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). https://doi.org/10.5555/3535850.3535899. [BibTeX]
Nieves Montes,  & Carles Sierra (2022). Synthesis and Properties of Optimally Value-Aligned Normative Systems. Journal of Artificial Intelligence Research, 74, 1739--1774. https://doi.org/10.1613/jair.1.13487. [BibTeX]
2021
Thiago Freitas Dos Santos,  Nardine Osman,  & Marco Schorlemmer (2021). Learning for Detecting Norm Violation in Online Communities. International Workshop on Coordination, Organizations, Institutions, Norms and Ethics for Governance of Multi-Agent Systems (COINE), co-located with AAMAS 2021 . https://arxiv.org/abs/2104.14911. [BibTeX]
2020
Nardine Osman,  Carles Sierra,  Ronald Chenu-Abente,  Qiang Shen,  & Fausto Giunchiglia (2020). Open Social Systems. Nick Bassiliades, Georgios Chalkiadakis, & Dave Jonge (Eds.), Multi-Agent Systems and Agreement Technologies (pp. 132--142). Springer International Publishing. [BibTeX]  [PDF]
Marta Poblet,  & Carles Sierra (2020). Understanding Help as a Commons. International Journal of the Commons, 14, 281--493. http://doi.org/10.5334/ijc.1029. [BibTeX]  [PDF]
Thiago Freitas Dos Santos
PhD Student
Joan Jené
Engineer
Phone Ext. 431837

Nardine Osman
Tenured Scientist
Phone Ext. 431826

Bruno Rosell
Engineer
Phone Ext. 431835

Marco Schorlemmer
Tenured Scientist
Phone Ext. 431858

Carles Sierra
Research Professor
Phone Ext. 431801