Towards Psychometrics-based Friend Recommendations in Social Networking Services

Two of the defining elements of Social Networking Services are the social profile, containing information about the user, and the social graph, containing information about the connections between users. Social Networking Services are used to connect to known people as well as to discover new contacts. Current friend recommendation mechanisms typically utilize the social graph. In this paper, we argue that psychometrics, the field of measuring personality traits, can help make meaningful friend recommendations based on an extended social profile containing collected smartphone sensor data. This will support the development of highly distributed Social Networking Services without central knowledge of the social graph.Comment: Accepted for publication at the 2017 International Conference on AI & Mobile Services (IEEE AIMS

Displaybook - Bringing online identity to situated displays

This work is part of a study in which we aim to explore multiple bridges between on-line and off-line forms of socialisation by creating bi-directional connections between Facebook and situated social interactions. In this paper, we specifically describe a study on the use of public displays for the public presentation of data from the Facebook profiles of people near the display. The key challenge is how to map the concept of sharing information within a social network, to the concept of sharing information with the places you visit. For this to be viable, people must have full control over what they share and in what circumstances they will share it. This paper addresses this issue by studying the sharing alternatives, how this sharing of profile data in a public display is perceived by people and what are the main factors affecting that perception. The results suggest that, overall, people seem to be willing to expose parts of their Facebook profiles if given proper privacy controls. However, the study has also revealed a clear gap between privacy control in Facebook and the type of privacy controls that would be needed for this particular use of Facebook information

Collaborating with Users in Proximity for Decentralized Mobile Recommender Systems

Typically, recommender systems from any domain, be it movies, music, restaurants, etc., are organized in a centralized fashion. The service provider holds all the data, biases in the recommender algorithms are not transparent to the user, and the service providers often create lock-in effects making it inconvenient for the user to switch providers. In this paper, we argue that the user's smartphone already holds a lot of the data that feeds into typical recommender systems for movies, music, or POIs. With the ubiquity of the smartphone and other users in proximity in public places or public transportation, data can be exchanged directly between users in a device-to-device manner. This way, each smartphone can build its own database and calculate its own recommendations. One of the benefits of such a system is that it is not restricted to recommendations for just one user - ad-hoc group recommendations are also possible. While the infrastructure for such a platform already exists - the smartphones already in the palms of the users - there are challenges both with respect to the mobile recommender system platform as well as to its recommender algorithms. In this paper, we present a mobile architecture for the described system - consisting of data collection, data exchange, and recommender system - and highlight its challenges and opportunities.Comment: Accepted for publication at the 2019 IEEE 16th International Conference on Ubiquitous Intelligence and Computing (IEEE UIC 2019

SocialRouting: The social-based routing algorithm for Delay Tolerant Networks

Delay and Disruptive Tolerant Networks (DTN) are relatively a new networking concept that could provide a robust communication in wide range of implementations from the space to battlefield or other military usage. However in such dynamic networks, which could be considered as a set of intermittently connected nodes, message forwarding strategy is a key issue. Existing routing solutions concentrate mainly on two major routing families flooding and knowledge based algorithms. This paper presents SocialRouting - the social-based routing algorithm designed for DTN. The use of the social properties of wireless mobile nodes is the novel way of message routing that is based on message ferrying between separated parts of the network. Proposed idea has been extensively tested using simulation tools. The simulations were made based on especially designed for measurements in DTN scenarios and compared with popular solutions

Online change detection for energy-efficient mobilec crowdsensing

Mobile crowdsensing is power hungry since it requires continuously and simultaneously sensing, processing and uploading fused data from various sensor types including motion sensors and environment sensors. Realizing that being able to pinpoint change points of contexts enables energy-efficient mobile crowdsensing, we modify histogram-based techniques to efficiently detect changes, which has less computational complexity and performs better than the conventional techniques. To evaluate our proposed technique, we conducted experiments on real audio databases comprising 200 sound tracks. We also compare our change detection with multivariate normal distribution and one-class support vector machine. The results show that our proposed technique is more practical for mobile crowdsensing. For example, we show that it is possible to save 80% resource compared to standard continuous sensing while remaining detection sensitivity above 95%. This work enables energy-efficient mobile crowdsensing applications by adapting to contexts

Using NFriendConnector to Extend Facebook to the Real World

This study presents a novel approach towards establishing online social connections using Facebook and NFC-enabled mobile phones. There is increasing convergence between users’ real life social networks and their online social networks, with online connections following actual social acquaintance and interactions. Accordingly there is a need to provide users with means of accessing and establishing online connections in social networking platforms such as Facebook as and when they interact with other people in their real lives. The NFriendConnector is a prototype application which fulfills this functionality. This paper describes the design and development of the prototype application. The expectation confirmation theory is used to analyze the extent to which the NFriendConnector fulfills this inherent need among users and how this influences their intention to adopt and use the prototype. The proposed research model is tested in an experimental setup