Improving QoE in multi-layer social sensing: A cognitive architecture and game theoretic model

Alessandro Di Stefano, Marialisa Scatà, Aurelio La Corte, Sajal K. Das, Pietro Liò

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a novel cognitive architecture and game-theoretic model for resource sharing among netizens, thus improving their quality of experience (QoE) in multi-layer social sensing environments. The underlying approach is to quantify micro-rewards and inequalities derived from social multi-layer interactions. Specifically, we model our society as a social multi-layer network of individuals or groups of individuals (nodes), where the layers represent multiple channels of interactions (on various services). The weighted edges correspond to the multiple social relationships between nodes participating in diferent services, refecting the importance assigned to each of these edges and are defned based on the concepts of awareness and homophily. Heterogeneity, both interactions-wise on the multiple layers and related to homophily between individuals, on each node and layer of a weighted multiplex network produces a complex multi-scale interplay between nodes in the multi-layer structure. Applying game theory, we quantify the impact of heterogeneity on the evolutionary dynamics of social sensing through a data driven approach based on the propagation of individual-level micro-afrmations and micro-inequalities. The micro-packets of energy continuously exchanged between nodes may impact positively or negatively on their social behaviors, producing peaks of extreme dissatisfaction and in some cases a form of distress. Quantifying the evolutionary dynamics of human behaviors enables the detection of such peaks in the population and enable us design a targeted control mechanism, where social rewards and self-healing help improve the QoE of the netizens.

Original languageEnglish
Title of host publicationSocialSense 2019 - Proceedings of the 2019 4th International Workshop on Social Sensing
EditorsGowri Sankar Ramachandran, Jorge Ortiz
PublisherAssociation for Computing Machinery, Inc
Pages18-23
Number of pages6
ISBN (Electronic)9781450367066
DOIs
Publication statusPublished - 15 Apr 2019
Event4th International Workshop on Social Sensing, SocialSense 2019 - Montreal, Canada
Duration: 15 Apr 2019 → …

Publication series

NameSocialSense 2019 - Proceedings of the 2019 4th International Workshop on Social Sensing

Conference

Conference4th International Workshop on Social Sensing, SocialSense 2019
CountryCanada
CityMontreal
Period15/04/19 → …

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  • Cite this

    Di Stefano, A., Scatà, M., La Corte, A., Das, S. K., & Liò, P. (2019). Improving QoE in multi-layer social sensing: A cognitive architecture and game theoretic model. In G. S. Ramachandran, & J. Ortiz (Eds.), SocialSense 2019 - Proceedings of the 2019 4th International Workshop on Social Sensing (pp. 18-23). (SocialSense 2019 - Proceedings of the 2019 4th International Workshop on Social Sensing). Association for Computing Machinery, Inc. https://doi.org/10.1145/3313294.3313384