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Challenging social media threats using collective well-being-aware recommendation algorithms and an educational virtual companion

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dc.contributor.author Ognibene, Dimitri
dc.contributor.author Wilkens, Rodrigo
dc.contributor.author Taibi, Davide
dc.contributor.author Hernández Leo, Davinia
dc.contributor.author Kruschwitz, Udo
dc.contributor.author Donabauer, Gregor
dc.contributor.author Theophilou, Emily
dc.contributor.author Lomonaco, Francesco
dc.contributor.author Bursic, Sathya
dc.contributor.author Lobo, René
dc.contributor.author Sánchez Reina, Jesús Roberto
dc.contributor.author Scifo, Lidia
dc.contributor.author Schwarze, Veronica
dc.contributor.author Börsting, Johanna
dc.contributor.author Hoppe, Ulrich
dc.contributor.author Aprin, Farbod
dc.contributor.author Malzahn, Nils
dc.contributor.author Eimler, Sabrina
dc.date.accessioned 2023-03-21T07:05:51Z
dc.date.available 2023-03-21T07:05:51Z
dc.date.issued 2023
dc.identifier.citation Ognibene D, Wilkens R, Taibi D, Hernández-Leo D, Kruschwitz U, Donabauer G, et al. Challenging social media threats using collective well-being-aware recommendation algorithms and an educational virtual companion. Front Artif Intell. 2023 Jan 9;5:654930. DOI: 10.3389/frai.2022.654930
dc.identifier.issn 2624-8212
dc.identifier.uri http://hdl.handle.net/10230/56293
dc.description.abstract Social media have become an integral part of our lives, expanding our interlinking capabilities to new levels. There is plenty to be said about their positive effects. On the other hand, however, some serious negative implications of social media have been repeatedly highlighted in recent years, pointing at various threats to society and its more vulnerable members, such as teenagers, in particular, ranging from much-discussed problems such as digital addiction and polarization to manipulative influences of algorithms and further to more teenager-specific issues (e.g., body stereotyping). The impact of social media—both at an individual and societal level—is characterized by the complex interplay between the users' interactions and the intelligent components of the platform. Thus, users' understanding of social media mechanisms plays a determinant role. We thus propose a theoretical framework based on an adaptive “Social Media Virtual Companion” for educating and supporting an entire community, teenage students, to interact in social media environments in order to achieve desirable conditions, defined in terms of a community-specific and participatory designed measure of Collective Well-Being (CWB). This Companion combines automatic processing with expert intervention and guidance. The virtual Companion will be powered by a Recommender System (CWB-RS) that will optimize a CWB metric instead of engagement or platform profit, which currently largely drives recommender systems thereby disregarding any societal collateral effect. CWB-RS will optimize CWB both in the short term by balancing the level of social media threats the users are exposed to, and in the long term by adopting an Intelligent Tutor System role and enabling adaptive and personalized sequencing of playful learning activities. We put an emphasis on experts and educators in the educationally managed social media community of the Companion. They play five key roles: (a) use the Companion in classroom-based educational activities; (b) guide the definition of the CWB; (c) provide a hierarchical structure of learning strategies, objectives and activities that will support and contain the adaptive sequencing algorithms of the CWB-RS based on hierarchical reinforcement learning; (d) act as moderators of direct conflicts between the members of the community; and, finally, (e) monitor and address ethical and educational issues that are beyond the intelligent agent's competence and control. This framework offers a possible approach to understanding how to design social media systems and embedded educational interventions that favor a more healthy and positive society. Preliminary results on the performance of the Companion's components and studies of the educational and psychological underlying principles are presented.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Frontiers
dc.relation.ispartof Frontiers in Artificial Intelligence. 2023 Jan 9;5:654930
dc.rights © 2023 Ognibene, Wilkens, Taibi, Hernández-Leo, Kruschwitz, Donabauer, Theophilou, Lomonaco, Bursic, Lobo, Sánchez-Reina, Scifo, Schwarze, Börsting, Hoppe, Aprin, Malzahn and Eimler. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Challenging social media threats using collective well-being-aware recommendation algorithms and an educational virtual companion
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.3389/frai.2022.654930
dc.subject.keyword Collective well-being
dc.subject.keyword Recommender systems
dc.subject.keyword Social media
dc.subject.keyword Virtual companion
dc.subject.keyword Social media threats
dc.subject.keyword Hierarchical reinforcement learning
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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