325,832 research outputs found
Evolving Social Networks via Friend Recommendations
A social network grows over a period of time with the formation of new
connections and relations. In recent years we have witnessed a massive growth
of online social networks like Facebook, Twitter etc. So it has become a
problem of extreme importance to know the destiny of these networks. Thus
predicting the evolution of a social network is a question of extreme
importance. A good model for evolution of a social network can help in
understanding the properties responsible for the changes occurring in a network
structure. In this paper we propose such a model for evolution of social
networks. We model the social network as an undirected graph where nodes
represent people and edges represent the friendship between them. We define the
evolution process as a set of rules which resembles very closely to how a
social network grows in real life. We simulate the evolution process and show,
how starting from an initial network, a network evolves using this model. We
also discuss how our model can be used to model various complex social networks
other than online social networks like political networks, various
organizations etc..Comment: 5 pages, 8 figures, 2 algorithm
Extraction and Analysis of Facebook Friendship Relations
Online Social Networks (OSNs) are a unique Web and social phenomenon, affecting tastes and behaviors of their users and helping them to maintain/create friendships. It is interesting to analyze the growth and evolution of Online Social Networks both from the point of view of marketing and other of new services and from a scientific viewpoint, since their structure and evolution may share similarities with real-life social networks. In social sciences, several techniques for analyzing (online) social networks have been developed, to evaluate quantitative properties (e.g., defining metrics and measures of structural characteristics of the networks) or qualitative aspects (e.g., studying the attachment model for the network evolution, the binary trust relationships, and the link prediction problem).\ud
However, OSN analysis poses novel challenges both to Computer and Social scientists. We present our long-term research effort in analyzing Facebook, the largest and arguably most successful OSN today: it gathers more than 500 million users. Access to data about Facebook users and their friendship relations, is restricted; thus, we acquired the necessary information directly from the front-end of the Web site, in order to reconstruct a sub-graph representing anonymous interconnections among a significant subset of users. We describe our ad-hoc, privacy-compliant crawler for Facebook data extraction. To minimize bias, we adopt two different graph mining techniques: breadth-first search (BFS) and rejection sampling. To analyze the structural properties of samples consisting of millions of nodes, we developed a specific tool for analyzing quantitative and qualitative properties of social networks, adopting and improving existing Social Network Analysis (SNA) techniques and algorithms
Evolution of the digital society reveals balance between viral and mass media influence
Online social networks (OSNs) enable researchers to study the social universe
at a previously unattainable scale. The worldwide impact and the necessity to
sustain their rapid growth emphasize the importance to unravel the laws
governing their evolution. We present a quantitative two-parameter model which
reproduces the entire topological evolution of a quasi-isolated OSN with
unprecedented precision from the birth of the network. This allows us to
precisely gauge the fundamental macroscopic and microscopic mechanisms
involved. Our findings suggest that the coupling between the real pre-existing
underlying social structure, a viral spreading mechanism, and mass media
influence govern the evolution of OSNs. The empirical validation of our model,
on a macroscopic scale, reveals that virality is four to five times stronger
than mass media influence and, on a microscopic scale, individuals have a
higher subscription probability if invited by weaker social contacts, in
agreement with the "strength of weak ties" paradigm
Network Structure Mining and Evolution Analysis - Based on BA Scale-Free Network Model
The massive adoption of the Internet facilitates growth of online social networks, in which information can be exchanged in a more efficient way. Such as products, user accounts, web pages, there may be a variety of objects suitable to structurize this kind of networks. As a result, this gives the networks complexity and dynamics. The work in this paper is aiming to studying the topological property of online social network structure from the aspect of dynamics, and make clear the evolution processes of the networks. This is done by a Mean-Field analysis of network growth based on BA Scale-Free network model. Data resources come from the Chinese online e-commerce platform you.163.com and graphs are modeled through commentator and mutual comments by calculating degree distribution of the networks. We build a growing random model for forecasting dynamics of degree evolution. Finally, we use data set on Sina Weibo to test the model and the results are satisfying
Power Structure and the Evolution of Social Networks in Massively Multiplayer Online Games
This paper examines the evolution of a social network in a Massively Multiplayer Online Game (MMOG) by modeling the players’ interaction network as a continuous-time markov chain. Results indicate that social hierarchy emerges out of an anarchical situation in which social actors participate voluntarily, have equal access to virtual resources from the beginning, cannot show their physical superiority and cannot show physical gestures during their communication / interaction. Our study findings hence contribute to the current interdisciplinary debate whether hierarchy is an emergent phenomenon that can be attributed to variations in individual qualities or whether hierarchy is an artificial outcome that is enacted on societies by parties that are privileged from birth
- …