In this chapter, the authors discuss the state-of-the-art of Geo-Social systems and Recommender systems, which are becoming extremely popular for users accessing social media trough mobile devices. Moreover, they introduce a general framework based on the interaction among those systems and the “Game With A Purpose” (GWAP) paradigm. The proposed framework/platform can help researchers to understand geo-social dynamics in order to design and test new services, such as recommenders of places of interest for tourists, real-time traffic information systems, personalized suggestions of social events, and so forth. To target the governance of such complexity, relevant data must be collected by the investigators, shared with the community, and analyzed to find dynamical patterns that correlate spatial-temporal information with the user’s preferences and objectives. The authors argue that the GWAP approach can be exploited to successfully satisfy many of these tasks.
For the scientific community, geo-social services are becoming increasingly important because they represent a new tool to shed light on the basic rules that govern human mobility, social behaviors, and context-aware attitudes. For example, understanding and predicting the position and the itinerary of (a group of) persons can help us to find ways to stop a virus contagion on a global scale, or to avoid traffic jams in metropolitan areas. Moreover, the optimization of the mobility of thousands or millions of people can influence urban design as well as ecological policies, because we can understand new ways to reduce superfluous air pollution and common resources consumption. In a nutshell, geo-social services can help us to build smarter cities, healthier citizens, and better quality of life.
Geo-Social services are usually implemented as Web applications as well as native apps for mobile environments, like iOS and Android. We can see these applications as platforms that make available different information which converge spontaneously into complex aggregated data (such as locations, social links, user’s interests and tagging activity over multimedia resources). To govern this complexity, researchers must collect and analyze users’ geo-located data, in order to understand geo-social dynamics.
In the procedure of collecting data, one of the problems that can teach us something about human dynamics, is that we usually deal with a kind of information that is sensible to be protected and we cannot violate user’s privacy in order to gather as much data as needed. Therefore, researchers must find ways to convince the user to communicate such data on a volunteering basis. If the user downloads an application that collects relevant information and sends it to a central storage system, we must be sure that the volunteer is willing to use such service. This means that the application should implement an appealing service, such as a game. In this scenario, a game is not just a side-product, but part of the process of acquiring information about users’ interests, attitudes, behaviors, and geographical position. Dynamical processes are really relevant, too: temporal data can be important as well as spatial observations, and real-time information is sometimes essential together with instruments for localization and social awareness. Another important feature of a geo-social application that addresses the collection of relevant data is the personalization of the service itself: the user must be aware that the service is returning information that is useful and enjoyable for him/her, in that location, and in the specific moment. Therefore, to give an example, if a car navigation system proposes a modification in the planned route, a valid reason must be communicated to the user. For example, a close friend is in the proximity, the temporary exhibition of her favorite painter is just few meters ahead, or—furthermore—a car incident has been detected two blocks ahead.
In this chapter, we propose an integrated framework, which can be used to analyze, design and test geo-social services that can meet the above requirements. In fact, we believe that the GWAP (game with a purpose) paradigm in the geo-social scenario can attract many volunteers by a way of appealing applications. Moreover, Recommender Systems (RS) are mature enough to provide personalization techniques that can be easily integrated with the proposed framework in order to filter out not relevant notifications.
The chapter is organized as follows. In the next section, we present the background and state of the art of the given research field. We present an overview of Geo-Social networks and describe Recommender Systems (focusing on the Collaborative Filtering approach) and their use to suggest useful information to the user. In addition, we present the GWAP approach as one of the implementation of the Crowdsourcing methodology for the gathering of big amount of users’ data. Merging together these three paradigms, afterwards we propose a framework that is helpful to analyze, design and test geo-social systems in their complexity. In particular, we describe the issues, the controversies, and the problems that arise, when we study such systems. Finally, we describe the building blocks of the integrated framework.