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

https://doi.org/10.1016/j.jocs.2017.06.009Get rights and content

Highlights

  • Data-driven research to study symbiotic networks.

  • study formations of social and physical networks.

  • First paper about Pokemon Go network.

Abstract

The recent popular game, Pokémon 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 Pokémon 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 Pokémon 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 Pokémon 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.

Introduction

The movie ‘The Matrix’ showed us a scene with two connected worlds: physical world and cyber virtual world. Characters can shuttle back and forth between the two worlds and interact with others. Nowadays, this fancy movie scene comes into being due to the emerging location-based mobile augmented reality (LMAR) techniques [1]. LMAR is changing the form of social networking from multiple aspects. Unlike traditional online social media and offline community, LMAR based social media requires users to physically attend to certain locations for interacting with others. People who interact online using avatars can also derive interactions in the real world when they are physically brought together by LMAR application. Therefore, LMAR has complicated the boundary of social networks, and it also cultivates brand-new forms of social networks. Accordingly, the cyber (virtual) world relationships and the real world connections of people evolve into two symbiotic social networks.

As one part of the symbiotic networks, the cyber social network states the relationships among the online avatars. At the same moment, an offline, location-sensitive physical social network rises among the corresponding users through face-to-face communication, greeting, or more generally, staying in a same area. The emerging mobile game Pokémon GO released by Niantic is a catalyst for symbiotic network formation. The game requires a player to arrive at certain places in order to interact with virtual game content. Players can also battle each other at the in-game facilities called gyms, which are usually pinned on landmark buildings of the real world. The battles between players in the cyber space form a cyber social network. On the other hand, since players need to stay in certain areas for playing, their interactions with other players in the real world form an offline physical social network. Hence, the cyber social network and the physical social network symbiotically affect each other.

Previous works about social network mainly focus on studying homogeneous social networks, including the structures, robustness, and user behaviours. The formation and effect of symbiotic social networks has not been deeply examined. Meanwhile, the study of symbiotic network formation can be of great importance to government decision making and society safety. Moreover, the formation of symbiotic social network can be used as a reference and tool in psychological research which studies the formation of social connection and the cognition of human relationship. Potentially, since Pokémon GO and alike applications have great capability to increase physical activity of individuals, this research may assist the analysis of the impact of LMAR on user health.

We carried out a data-driven research to study the symbiotic networks formed by the offline interactions of users and the online connections of the avatars. We studied the properties, user behaviour, and formation of such novel social networks. Accordingly, we used two real datasets in our research. First, we designed a questionnaire to collect Pokémon GO players’ individual behaviours in Pokémon GO. Maps of Melbourne were then introduced to track and record players’ usual playing areas. Second, we employed pedestrian count data imported from sensors distributed across Melbourne CBD to reflect social behaviours that differ from that of players. Based on the Pokémon dataset, we first built a symbiotic social network of Pokémon GO players. The building process models and simulates the formation of social interaction among the players. Second, we analysed the relationship between the formation of the virtual network and the physical network. Next, we investigated how the social behaviours changed after the symbiotic network emerged. According to our experiment, the popular socialising locations of people have drastically changed after the interference of Pokémon GO. Our work is essential for modelling the information diffusion, the user behaviours, or the impact of AR/VR on human interaction in symbiosis social networks.

In this paper, we study the formation, symbiosis and impact of two networks, which are the virtual social network of in-game characters, and the social network of players in the physical world. The paper is organised as follows: methods for collecting and analysing data are presented in Sections 2 and 3. Outcomes of data analysis are exhibited in Section 4. Related works are introduced in Section 5. Finally, this paper is concluded in Section 6.

Section snippets

Dataset 1: Pokémon GO Data 5

To investigate the formation of the symbiotic social networks of Pokémon GO player and the symbiosis of the networks, we designed a survey including the related questions.

Dataset 2: pedestrian data6

We use the pedestrian dataset to study the impact of the cyber social network to the structure of the physical world in terms of population distribution in the city area. The data is collected by 43 sensors distributed across Melbourne city. These sensors return pedestrian counts of the previous hour monthly. The data has been collected from year 2009 to date. The dataset includes 1000 sensor records totally, each of which contains the latitude and longitude of the sensor, collecting date/time,

Preliminary analysis on questionnaire and location

In this section, we present the statistics of the survey participants and their playing behaviours according to the questionnaires. Participants are anonymised for privacy considerations. As shown in Table 2, 75% of the 104 respondents played Pokémon GO every hour or every day, while there were only around 15.38% of the players challenged gym at the same frequency. It is deduced that players were much less frequent in challenging gym than catching Pokémon.

Next, we analysed the characteristics

Related work

The characteristics and interactions of traditional online/offline social networks have been exclusively analysed. On the other hand, the perception regarding location based mobile AR applications is evolving. It is of interest to understand how AR can affect social behaviour of users, and what the characteristics of the social network would then have. We provide a brief review of the research about social network characteristics and location based AR. As the latest phenomenal LMAR application,

Conclusion

In this paper, we analysed the symbiosis and characteristics of symbiotic social networks among users of a location based augmented reality application. For studying symbiotic social network formation, we collected a Pokémon GO player dataset which contains the player demographics, playing behaviours, and playing locations. By incorporating real world pedestrian count data, we studied the change on social behaviour brought by symbiotic social network in terms of spatial hot-spot deriving social

Acknowledgements

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.

Derek Wang received his Bachelor degree of Engineering from Huazhong University of Science and Technology (HUST), China (2011); MSc by research degree from Deakin University, Australia (2016). Currently, he is a PhD student with Deakin University and CSIRO Data61, Australia. His research interests include machine learning, advanced deep neural network, and application of deep learning in complex network, social networking security, distributed system security, and network risk assessment.

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    Derek Wang received his Bachelor degree of Engineering from Huazhong University of Science and Technology (HUST), China (2011); MSc by research degree from Deakin University, Australia (2016). Currently, he is a PhD student with Deakin University and CSIRO Data61, Australia. His research interests include machine learning, advanced deep neural network, and application of deep learning in complex network, social networking security, distributed system security, and network risk assessment.

    Tingmin Wu received the Bachelor of Information Technology degree (with first class Hons.) from Deakin University Australia in 2016. She is working toward the PhD degree at the School of Information Technology, Deakin University. Her research interests include cyber security, especially in social spam detection.

    Dr. Sheng Wen received the degree in computer science from the Central South University of China in 2012, and the Ph.D. degree from the School of Information Technology, Deakin University, Australia, in 2015. Since then, he has been a Lecturer with Deakin University. His focus is on modeling of virus spread, information dissemination, and defense strategies for the Internet threats. He is also interested in the techniques of identifying information sources in networks.

    Prof. Yang Xiang received his PhD in Computer Science from Deakin University, Australia. He is the Director of Centre for Cyber Security Research, Deakin University. His research interests include network and system security, data analytics, distributed systems, and networking. In particular, he is currently leading his team developing active defense systems against large-scale distributed network attacks. He is the Chief Investigator of several projects in network and system security, funded by the Australian Research Council (ARC). He has published more than 200 research papers in many international journals and conferences. Prof Yang is a Senior Member of the IEEE.

    Prof. Wanlei Zhou received the B.Eng and M.Eng degrees from Harbin Institute of Technology, Harbin, China in 1982 and 1984, respectively, and the PhD degree from The Australian National University, Canberra, Australia, in 1991, all in Computer Science and Engineering. He also received a DSc degree (a higher Doctorate degree) from Deakin University in 2002. He is currently the Alfred Deakin Professor (the highest honour the University can bestow on a member of academic staff), Chair of Information Technology, and Associate Dean (International Research Engagement) of Faculty of Science, Engineering and Built Environment, Deakin University. Professor Zhou has been the Head of School of Information Technology twice (January 2002–Apr 2006 and Jan 2009–Jan 2015) and Associate Dean of Faculty of Science and Technology in Deakin University (May 2006–Dec 2008). His research interests include distributed systems, network security, bioinformatics, and e-learning. Professor Zhou has published more than 300 papers in refereed international journals and refereed international conferences proceedings. He is a Senior Member of the IEEE.

    Prof. Houcine Hassan is associate Professor of the Department of Computer Engineering in the Polytechnic University of Valencia, Spain, since 1994. He received a MS and PhD degree in Computer Engineering from the Polytechnic University of Valencia, in 1993 and 2001 respectively. He joined the Industrial Informatics group in 1993, where he is participating in several research projects. His research interests covers a number of aspects of the development of hardware and software architectures including real-time systems support, embedded systems, hardware/software co-design, ubiquitous computing, AI agent based systems, autonomous systems, sensor networks, robotic architectures, behaviour and emotional systems, application and scheduling integration, QoS.

    Dr. Abdulhameed Al-Eliwi got his PhD in Software Engineering, College of Engineering, Florida Institute of Technology-Melbourne, USA, 2002. He got his MSc in Computer Science (Information Systems), College of Engineering, Florida Institute of Technology-Melbourne, USA, 1998, and MSc in Engineering Management (Systems Engineering), College of Engineering, Florida Institute of Technology-Melbourne, USA, 2003. His BSc was also in Computer Information Systems with Honor, College of Computer and Information Science, KSU, Saudi Arabia, Riyadh 1992.

    1

    Address: Centre of Cyber Security Research, Deakin University, Australia.

    2

    Address: Data 61, CSIRO, Australia.

    3

    Address: Polytechnic University of Valencia, Camino de Vera, s/n 46022, Valencia, Spain.

    4

    Address: King Saud University, Riyadh 11543, Saudi Arabia.

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