53 research outputs found
Living City, A Collaborative Browser-Based Massively Multiplayer Online Game
This work presents the design and implementation of our Browser-based Massively Multiplayer Online Game, Living City, a simulation game fully developed at the University of Messina. Living City is a persistent and real-time digital world, running in the Web browser environment and accessible from users without any client-side installation. Today Massively Multiplayer Online Games attract the attention of Computer Scientists both for their architectural peculiarity and the close interconnection with the social network phenomenon. We will cover these two aspects paying particular attention to some aspects of the project: game balancing (e.g. algorithms behind time and money balancing); business logic (e.g., handling concurrency, cheating avoidance and availability) and, finally, social and psychological aspects involved in the collaboration of players, analyzing their activities and interconnections
A Framework for Designing 3d Virtual Environments
The process of design and development of virtual environments can be supported by tools and frameworks, to save time in technical aspects and focusing on the content. In this paper we present an academic framework which provides several levels of abstraction to ease this work. It includes state-of-the-art components we devised or integrated adopting open-source solutions in order to face specific problems. Its architecture is modular and customizable, the code is open-source.\u
Analyzing the Facebook Friendship Graph
Online Social Networks (OSN) during last years acquired a\ud
huge and increasing popularity as one of the most important emerging Web phenomena, deeply modifying the behavior of users and contributing to build a solid substrate of connections and relationships among people using the Web. In this preliminary work paper, our purpose is to analyze Facebook, considering a signi�cant sample of data re\ud
ecting relationships among subscribed users. Our goal is to extract, from this platform, relevant information about the distribution of these relations and exploit tools and algorithms provided by the Social Network Analysis (SNA) to discover and, possibly, understand underlying similarities\ud
between the developing of OSN and real-life social networks
Improving Recommendation Quality by Merging Collaborative Filtering and Social Relationships
Matrix Factorization techniques have been successfully applied to raise the quality of suggestions generated\ud
by Collaborative Filtering Systems (CFSs). Traditional CFSs\ud
based on Matrix Factorization operate on the ratings provided\ud
by users and have been recently extended to incorporate\ud
demographic aspects such as age and gender. In this paper we\ud
propose to merge CF techniques based on Matrix Factorization\ud
and information regarding social friendships in order to\ud
provide users with more accurate suggestions and rankings\ud
on items of their interest. The proposed approach has been\ud
evaluated on a real-life online social network; the experimental\ud
results show an improvement against existing CF approaches.\ud
A detailed comparison with related literature is also presen
On Facebook, most ties are weak
Pervasive socio-technical networks bring new conceptual and technological
challenges to developers and users alike. A central research theme is
evaluation of the intensity of relations linking users and how they facilitate
communication and the spread of information. These aspects of human
relationships have been studied extensively in the social sciences under the
framework of the "strength of weak ties" theory proposed by Mark Granovetter.13
Some research has considered whether that theory can be extended to online
social networks like Facebook, suggesting interaction data can be used to
predict the strength of ties. The approaches being used require handling
user-generated data that is often not publicly available due to privacy
concerns. Here, we propose an alternative definition of weak and strong ties
that requires knowledge of only the topology of the social network (such as who
is a friend of whom on Facebook), relying on the fact that online social
networks, or OSNs, tend to fragment into communities. We thus suggest
classifying as weak ties those edges linking individuals belonging to different
communities and strong ties as those connecting users in the same community. We
tested this definition on a large network representing part of the Facebook
social graph and studied how weak and strong ties affect the
information-diffusion process. Our findings suggest individuals in OSNs
self-organize to create well-connected communities, while weak ties yield
cohesion and optimize the coverage of information spread.Comment: Accepted version of the manuscript before ACM editorial work. Check
http://cacm.acm.org/magazines/2014/11/179820-on-facebook-most-ties-are-weak/
for the final versio
- …