Elsevier

Pervasive and Mobile Computing

Volume 25, January 2016, Pages 67-87
Pervasive and Mobile Computing

SocialCRC: Enabling socially-consensual rendezvous coordination by mobile phones

https://doi.org/10.1016/j.pmcj.2015.07.006Get rights and content

Abstract

Rendezvous is a common life event to bring people together for social interaction. The previous research on rendezvous coordination considers location-specific information but seldom takes into account the mutual social influence of individual attendees in the coordination process. By considering contextual information and social relationship among attendees, this study presents a new mobile application, called SocialCRC, which identifies a more satisfactory rendezvous point. This study conducts comprehensive evaluations on SocialCRC. Results indicate that SocialCRC offers satisfactory results for the most socially influential person while not significantly diminishing the satisfaction of the least socially influential person involved in the coordination process.

Introduction

Social networks play an important role in influencing people’s thoughts and actions  [1], [2]. A number of social networking websites, such as MySpace  [3], Orkut  [4], and Facebook  [5], have emerged in the past few years. These websites offer users a wide range of interesting applications for expanding their social circles. The development of mobile social applications  [6], [7]and location-based services (LBS)  [8] is likely to route regular social activities through this ubiquitous mobile sensing platform, transforming them into opportunities for serendipitous connectivity, i.e., occasions to rendezvous in a wider range of contexts than previously possible via conventional computing systems. Particularly, commensality, or the practice of eating together, is a social activity that offers many opportunities for interacting with family and friends  [9]. To rapidly enable socially-consensual rendezvous coordination for impromptu gatherings   [10] (e.g., setting up a meal gathering with nearby friends and/or family members tonight), this study demonstrates the use of an innovative mobile coordination system (i.e., SocialCRC) for setting up impromptu gatherings. Given the ubiquity of mobile phones in our everyday lives, this phone-based approach offers users more opportunities to invite nearby friends for a rendezvous and eases the rendezvous coordination by dynamically recommending a socially-consensual location.

Existing mobile social applications  [6], [7] or location-based systems  [8] focus on location-specific information in geographic coordination. These systems select a rendezvous point based on only contextual information, and do not consider social influence   [1], [2], which represents the other intrinsic factors impacting people’s thoughts or actions. Social influence occurs when other people affect an individual’s thoughts or actions through the qualitatively different ways of attitude change. As described in  [2], people are influenced by others in the form of compliance, identification, or internalization to change their behavior, i.e., induced behavior. Through adopting the induced behavior, they can gain rewards or avoid punishments from a powerful influencing person, establish/maintain relationship with other people, or gain satisfaction derived from internalization. The concept of the mutual social influence in dynamic groups of people has been widely applied to enable a variety of personalized multimedia applications, such as social video  [11], privacy preserving  [12], and friend making at social events  [13], [14], [15]. Imagine the following scenario:

Jane and Ben are interested in Japanese culture, and they are planning a trip to Japan. One day, with the help of their location-aware mobile devices, they find a Japanese friend in their vicinity. They invite their Japanese friend and several other nearby friends to dinner so that they can exchange notes on Japan. They first call each individual to check his/her current location, availability and preference towards restaurants. After they confirm everyone’s location and availability through a large number of phone calls, they finally decide to meet at a Thai-food restaurant located close to all the invitees and inform them the rendezvous point by making more phone calls. These interactions are called microcoordination   [16]. Now, imagine that their Japanese friend dislikes Thai food. Naturally, he/she may be not pleased to attend. If he/she finally declines the invitation, Jane and Ben end up losing an opportunity to meet with a key person for discussing their travel plans. As a result, they may even cancel the rendezvous entirely.

The microcoordination process requires tedious interactions through phone calls on inquiring all friends’ contextual information to coordinate a rendezvous. Furthermore, through the identification process defined in  [2], the choice of a rendezvous point can significantly influence the preferred person’s willingness to attend an event. Because other individuals want to maintain a satisfactory relationship with the preferred person, the attendance of the preferred person will in turn affect the opportunity to rendezvous. This can create a considerable amount of stress for the host while selecting the rendezvous point. To overcome these problems, this study proposes a social- and context-aware rendezvous coordination system, called SocialCRC, which enables smooth microcoordination and reduces the burden of individually contacting members by facilitating a consensual situation.

The main contributions of this paper are three-fold.

  • This study identifies the current lack of considering the impact of social influence in the microcoordination process and then proposes the UserRank algorithm to calculate the social influence of each attendee from social relationship among all rendezvous attendees. By incorporating attendees’ real-time contextual information, recent personal preferences towards other attendees or cuisine types, and long-term social relationship among attendees, a socially-consensual ranking list of rendezvous points can be obtained.

  • This study designs and implements an integrated mobile phone-based system, SocialCRC, to assist users in coordinating everyday rendezvous activities (i.e., impromptu gatherings) in their daily life. By inviting nearby friends shown on a customized user interface, users can easily coordinate their impromptu gatherings through finding a socially-consensual rendezvous point dynamically recommended by the system, instead of using traditional techniques of rendezvous coordinations (e.g., exchanging multiple emails and making lots of phone calls).

  • This study reveals insights on developing impromptu rendezvousing applications by conducting an extensive set of user study and simulations over different groups of participants to gather their opinions on rendezvousing, and then evaluates objective recommendation quality, user satisfaction levels, and final feedback towards SocialCRC. The user study indicates that SocialCRC offers satisfactory results for the most influential person involved in the coordination process, and provides an acceptable solution for the entire group, without significantly diminishing the satisfaction of the least influential person in the group. Moreover, the results of Simulation I validate that SocialCRC actually reflects the participants’ social influence levels by opportunistically degrading the user convenience of attendees with lower values of social influences in each round, especially that of the least influential person, to ensure the user convenience of attendances with higher values of social influences. To validate how SocialCRC operates under larger group sizes, the results of Simulation II indicate that the mechanism of updating the social relationship in SocialCRC can quickly capture the intrinsic social influence among the users. Also, because an increasing number of attendance records will be logged into the content database, the speed to learn the real social relationship between users becomes faster as the group size increases.

The rest of this paper is organized as follows. Section  2 reviews related work. Section  3 describes the design and implementation of the mobile phone-based application called SocialCRC. Section  4 provides details about the SocialCRC recommender algorithm. Section  5 conducts a field study involving 8 small-sized (3-person) and 4 medium-sized (4-person) groups to validate the effectiveness of SocialCRC, while Sections  6 Simulation I: validating the impact of social influences, 7 Simulation II: convergence analysis of social influence present two sets of simulations to further explore the impact of social influences and how the system operates under larger group sizes. Section  8 summarizes the implications drawn from this study for guiding future studies of impromptu rendezvousing application design. Finally, Section  9 offers conclusions and directions for future work.

Section snippets

Social influence

Researchers have identified social influence  [1], [2] as an intrinsic social effect that occurs when group interaction affects a person’s thoughts or actions. Hui et al.  [17] presented a horizontal view of social influence and conducted a quantitative study of neighbor’s influence on a particular node joining a group of popular online social networks (OSNs). They proposed a simple social influence model to describe and explain the group joining process of users on OSNs, and found that a set

System architecture and design

The goal of the SocialCRC system is to facilitate people to invite nearby friends, collect personal preferences of all attendees, and finally inform all attendees a list of socially-consensus rendezvous points through their smartphones. The SocialCRC system is based on the client–server architecture shown in Fig. 1. People use their smartphones installed the client-side phone application of SocialCRC to coordinate a rendezvous. Based on attendees’ real-time context, recent personal preferences,

SocialCRC recommender

Fig. 4 presents the design of the rendezvous point recommender. The goal of the rendezvous point recommender is to generate a list of rendezvous points ordered by the values of weighted scores integrating the personal preferences given by all attendees. The module first generates a personal ranking list of rendezvous points ordered by the ranking scores derived from user’s current location and time (abbreviated as real-time context). Because the attendance decisions of the influential persons

User study

This section describes the design of the user study. First, several groups of participants were recruited to perform the field study. Then, a formal study procedure was used to demonstrate that SocialCRC facilitates socially-aware rendezvous microcoordination. Finally, the evaluation metrics to assess the performance of SocialCRC were defined. The findings of this user study include: (1) SocialCRC is able to objectively reflect users’ social influence levels; (2) SocialCRC provides a

Simulation I: validating the impact of social influences

To further validate that the decrease of the overall user convenience was actually caused by the decrease of participants’ social influence levels, we performed a simulation with the participants’ social influence and context conditions recorded in the previous user study. The experimental setup and results are presented as follows.

Simulation II: convergence analysis of social influence

To evaluate how the system operates under larger group sizes, and also to examine if the proposed system can well capture the social influence of attendees, we performed another simulation by reusing the participants’ social influence and context conditions recorded in the previous user study. In a real system, it is not applicable to ask users to specify how influential their friends are to them, since the process is time-consuming, and they need to update this information again when a new

Discussions

This section discusses pros and cons of our current design and provides further design implications for building social group applications as follows.

Conclusions and future work

This study presents a new online application, SocialCRC, to ease rendezvous microcoordination for mobile users. The UserRank algorithm calculates the social influence of each attendee based on the social relationship between rendezvous attendees. By considering social influence of rendezvous attendees, SocialCRC can suggest a satisfactory rendezvous point. This study applies SocialCRC to the context of a dinner rendezvous. After designing and implementing this system, this study conducts an

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