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Pokemon GO in Melbourne CBD: A case study of the cyber-physical symbiotic social networks

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Pokemon GO in Melbourne CBD: A case study of the cyber-physical symbiotic social networks

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dc.contributor.author Wang, Derek es_ES
dc.contributor.author Wu, Tingmin es_ES
dc.contributor.author Wen, Sheng es_ES
dc.contributor.author Liu, Donghai es_ES
dc.contributor.author Xiang, Yang es_ES
dc.contributor.author Zhou, Wanlei es_ES
dc.contributor.author Hassan Mohamed, Houcine es_ES
dc.contributor.author Alelaiwi, Abdulhameed es_ES
dc.date.accessioned 2020-07-07T03:33:22Z
dc.date.available 2020-07-07T03:33:22Z
dc.date.issued 2018-05 es_ES
dc.identifier.issn 1877-7503 es_ES
dc.identifier.uri http://hdl.handle.net/10251/147539
dc.description.abstract [EN] The recent popular game, Pokemon GO, created two symbiotic social networks by location-based mobile augmented reality (LMAR) technique. One is in the physical world among players, and another one is in the cyber world among players' avatars. To date, there is no study that has explored the formation of each social network and their symbiosis. In this paper, we carried out a data-driven research on the Pokemon GO game to solve this problem. We accordingly organised the collection of two real datasets. For the first dataset, we designed a questionnaire to collect players' individual behaviours in Pokemon GO, and used maps of Melbourne (Australia) to track and record their usual playing areas. Based on the data that we collected, we modelled the formation of the symbiotic social networks in both physical world (i.e. for players) and cyber world (i.e. for avatars) as well as interactions between players and Pokemon GO elements (i.e. 'bridges' of the two worlds). By investigating the mechanism of network formation, we revealed the relatively weak correlation between the formation processes of the two networks. We further incorporated the real-world pedestrian dataset collected by sensors across Melbourne CBD into the study of their symbiosis. Based on the second dataset, we examined the changes of people's social behaviours in terms of most visited places. The results suggested that the existence of the cyber social network has reciprocally changed the structure of the symbiotic physical social network. (C) 2017 Elsevier B.V. All rights reserved. es_ES
dc.description.sponsorship This research is partially supported by the Australian Research Council projects DP150103732, DP140103649, and LP140100816. The authors extend their appreciation to the International Scientific Partnership Program (ISPP) at King Saud University, Riyadh, Saudi Arabia for funding this work through the project No. ISPP#0069. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Journal of Computational Science es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Social network es_ES
dc.subject Augmented reality es_ES
dc.subject Pokemon GO es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Pokemon GO in Melbourne CBD: A case study of the cyber-physical symbiotic social networks es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.jocs.2017.06.009 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/ARC/Discovery Projects/DP140103649/AU/Discovery Projects - Grant ID: DP140103649/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/KSU//ISPP0069/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/ARC/Discovery Projects/DP150103732/AU/Discovery Projects - Grant ID: DP150103732/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/ARC/Linkage Projects/LP140100816/AU/Linkage Projects - Grant ID: LP140100816/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.description.bibliographicCitation Wang, D.; Wu, T.; Wen, S.; Liu, D.; Xiang, Y.; Zhou, W.; Hassan Mohamed, H.... (2018). Pokemon GO in Melbourne CBD: A case study of the cyber-physical symbiotic social networks. Journal of Computational Science. 26:456-467. https://doi.org/10.1016/j.jocs.2017.06.009 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.jocs.2017.06.009 es_ES
dc.description.upvformatpinicio 456 es_ES
dc.description.upvformatpfin 467 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 26 es_ES
dc.relation.pasarela S\379951 es_ES
dc.contributor.funder King Saud University, Arabia Saudí es_ES


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