Cityware

2010 ◽  
pp. 911-919 ◽  
Author(s):  
Vassilis Kostakos ◽  
Eamonn O’Neill
Keyword(s):  
Social Networks ◽  
Real World ◽  
Online Social Networks ◽  
Social Data

In this paper, we describe a platform that enables us to systematically study online social networks alongside their real-world counterparts. Our system, entitled Cityware, merges users’ online social data, made available through Facebook, with mobility traces captured via Bluetooth scanning. Furthermore, our system enables users to contribute their own mobility traces, thus allowing users to form and participate in a community. In addition to describing Cityware’s architecture, we discuss the type of data we are collecting, and the analyses our platform enables, as well as users’ reactions and thoughts.

Cityware

2011 ◽  
pp. 196-205 ◽  
Author(s):  
Vassilis Kostakos ◽  
Eamonn O’Neill
Keyword(s):  
Social Networks ◽  
Real World ◽  
Online Social Networks ◽  
Social Data

In this paper, we describe a platform that enables us to systematically study online social networks alongside their real-world counterparts. Our system, entitled Cityware, merges users’ online social data, made available through Facebook, with mobility traces captured via Bluetooth scanning. Furthermore, our system enables users to contribute their own mobility traces, thus allowing users to form and participate in a community. In addition to describing Cityware’s architecture, we discuss the type of data we are collecting, and the analyses our platform enables, as well as users’ reactions and thoughts.

Information Attacks and Defenses on the Social Web

2018 ◽  
pp. 216-235
Author(s):  
Agostino Poggi ◽  
Michele Tomaiuolo
Keyword(s):  
Social Networks ◽  
Social Networking ◽  
Real World ◽  
Web Sites ◽  
Online Social Networks ◽  
Social Web ◽  
Security Measures ◽  
The Social ◽  
Attacks And Defenses ◽  
Interest In Technology

Social web sites are used daily by many millions of users. They have attracted users with very weak interest in technology, including absolute neophytes of computers in general. Common users of social web sites often have a carefree attitude in sharing information. Moreover, some system operators offer sub-par security measures, which are not adequate for the high value of the published information. For all these reasons, online social networks suffer more and more attacks by sophisticated crackers and scammers. To make things worse, the information gathered from social web sites can trigger attacks to even more sensible targets. This work reviews some typical social attacks that are conducted on social networking systems, describing real-world examples of such violations and analyzing in particular the weakness of password mechanisms. It then presents some solutions that could improve the overall security of the systems.

Collective Solitude and Social Networks in World of Warcraft

2009 ◽  
pp. 78-100 ◽  
Author(s):  
Nicolas Ducheneaut
Keyword(s):  
Social Networks ◽  
Real World ◽  
Online Social Networks ◽  
Online Games ◽  
World Of Warcraft ◽  
Massively Multiplayer Online Games ◽  
Multiplayer Online Games ◽  
The Relationship ◽  
Do So ◽  
Massively Multiplayer

This chapter investigates the nature and structure of social networks formed between the players of massively multiplayer online games (MMOGs), an incredibly popular form of Internet-based entertainment attracting millions of subscribers. To do so, we use data collected about the behavior of more than 300,000 characters in World of Warcraft (the most popular MMOG in America). We show that these social networks are often sparse and that most players spend time in the game experiencing a form of “collective solitude”: they play surrounded by, but not necessarily with, other players. We also show that the most successful player groups are analogous to the organic, team-based forms of organization that are prevalent in today’s workplace. Based on these findings, we discuss the relationship between online social networks and “real-world” behavior in organizations in more depth.

Parallel Greedy Algorithm to Multiple Influence Maximization in Social Network

2021 ◽  
Vol 15 (3) ◽  
pp. 1-21
Author(s):  
Guanhao Wu ◽  
Xiaofeng Gao ◽  
Ge Yan ◽  
Guihai Chen
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Parallel Algorithms ◽  
Real World ◽  
Online Social Networks ◽  
Heuristic Algorithms ◽  
Influence Maximization ◽  
Memory Overhead ◽  
Influence Spread ◽  
Real World Applications

Influence Maximization (IM) problem is to select influential users to maximize the influence spread, which plays an important role in many real-world applications such as product recommendation, epidemic control, and network monitoring. Nowadays multiple kinds of information can propagate in online social networks simultaneously, but current literature seldom discuss about this phenomenon. Accordingly, in this article, we propose Multiple Influence Maximization (MIM) problem where multiple information can propagate in a single network with different propagation probabilities. The goal of MIM problems is to maximize the overall accumulative influence spreads of different information with the limit of seed budget . To solve MIM problems, we first propose a greedy framework to solve MIM problems which maintains an -approximate ratio. We further propose parallel algorithms based on semaphores, an inter-thread communication mechanism, which significantly improves our algorithms efficiency. Then we conduct experiments for our framework using complex social network datasets with 12k, 154k, 317k, and 1.1m nodes, and the experimental results show that our greedy framework outperforms other heuristic algorithms greatly for large influence spread and parallelization of algorithms reduces running time observably with acceptable memory overhead.

Information and Password Attacks on Social Networks

2015 ◽  
Vol 8 (1) ◽  
pp. 25-42 ◽  
Author(s):  
Enrico Franchi ◽  
Agostino Poggi ◽  
Michele Tomaiuolo
Keyword(s):  
Social Networks ◽  
Social Networking ◽  
Real World ◽  
Online Social Networks ◽  
Social Engineering ◽  
Security Measures ◽  
Old Friends ◽  
The Way

Online social networks have changed the way people interact, allowing them to stay in touch with their acquaintances, reconnect with old friends, and establish new relationships with other people based on hobbies, interests, and friendship circles. Unfortunately, the regrettable concurrence of the users' carefree attitude in sharing information, the often sub-par security measures from the part of the system operators and, eventually, the high value of the published information make online social networks an interesting target for crackers and scammers alike. The information contained can be used to trigger attacks to even more sensible targets and the ultimate goal of sociability shared by the users allows sophisticated forms of social engineering inside the system. This work reviews some typical social attacks that are conducted on social networking systems, carrying real-world examples of such violations and analysing in particular the weakness of password mechanisms. It then presents some solutions that could improve the overall security of the systems.

Understanding Weight Change Behaviors through Online Social Networks

2011 ◽  
Vol 2 (3) ◽  
pp. 46-69 ◽  
Author(s):  
Xiaoxiao Ma ◽  
Guanling Chen ◽  
Juntao Xiao
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Influence ◽  
Empirical Analysis ◽  
Real World ◽  
Weight Change ◽  
Online Social Networks ◽  
Community Support ◽  
Propagation Distance ◽  
Weight Changes

Online Social Networks (OSNs) provide a good way to make connections with people with similar interests and goals. In particular, health-centered OSNs are emerging to provide knowledge and support for those interested in managing their own health. This paper provides an empirical analysis of a health OSN, which allows its users to record their foods and exercises, track their diet progress toward weight-change goals, and socialize and group with each other for community support. Based on about five month data collected from more than 107,000 users, the authors studied their weigh-in behaviors and tracked their weight-change progress. The authors found that the users’ weight changes correlated positively with the number of weigh-ins, the number of their friends, and their friends’ weight-change performance. The authors also show that the users’ weight changes have rippling effects in the OSN due to social influence. The strength of such online influence and its propagation distance appear to be greater than those in a real-world social network.

Exploring the Properties of Online Social Network Data and Their Implications for Consumer Social Data Analytics

2014 ◽  
pp. 210-230
Author(s):  
Yamen Koubaa
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Consumer Behavior ◽  
Online Social Networks ◽  
Data Analytics ◽  
Online Social Network ◽  
Network Data ◽  
Social Data ◽  
Social Network Data ◽  
Consumer Data

The prediction of consumer behavior is largely based on the analysis of consumer data using statistics as a tool for prediction. Thanks to online social networks, large quantities of heterogeneous consumer data are now available at competitive costs. Though they have much in common with conventional data, online social network datasets display several different properties. The exploration of these unique properties is indispensable to insuring the accuracy of predictions and data analytics. This chapter presents online social data, discusses seven properties of online social network data, suggests some analysis tools, and draws implications regarding the use of social data analytics.

Understanding Weight Change Behaviors through Online Social Networks

2012 ◽  
pp. 189-214
Author(s):  
Xiaoxiao Ma ◽  
Guanling Chen ◽  
Juntao Xiao
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Influence ◽  
Empirical Analysis ◽  
Real World ◽  
Weight Change ◽  
Online Social Networks ◽  
Community Support ◽  
Propagation Distance ◽  
Weight Changes

Online Social Networks (OSNs) provide a good way to make connections with people with similar interests and goals. In particular, health-centered OSNs are emerging to provide knowledge and support for those interested in managing their own health. This paper provides an empirical analysis of a health OSN, which allows its users to record their foods and exercises, track their diet progress toward weight-change goals, and socialize and group with each other for community support. Based on about five month data collected from more than 107,000 users, the authors studied their weigh-in behaviors and tracked their weight-change progress. The authors found that the users’ weight changes correlated positively with the number of weigh-ins, the number of their friends, and their friends’ weight-change performance. The authors also show that the users’ weight changes have rippling effects in the OSN due to social influence. The strength of such online influence and its propagation distance appear to be greater than those in a real-world social network.

scholarly journals Bots increase exposure to negative and inflammatory content in online social systems

2018 ◽  
Vol 115 (49) ◽  
pp. 12435-12440 ◽  
Author(s):  
Massimo Stella ◽  
Emilio Ferrara ◽  
Manlio De Domenico
Keyword(s):  
Social Networks ◽  
Complex Systems ◽  
Online Social Networks ◽  
Social System ◽  
Large Scale ◽  
Social Conflict ◽  
Social Systems ◽  
Social Data ◽  
The Social ◽  
Peripheral Areas

Societies are complex systems, which tend to polarize into subgroups of individuals with dramatically opposite perspectives. This phenomenon is reflected—and often amplified—in online social networks, where, however, humans are no longer the only players and coexist alongside with social bots—that is, software-controlled accounts. Analyzing large-scale social data collected during the Catalan referendum for independence on October 1, 2017, consisting of nearly 4 millions Twitter posts generated by almost 1 million users, we identify the two polarized groups of Independentists and Constitutionalists and quantify the structural and emotional roles played by social bots. We show that bots act from peripheral areas of the social system to target influential humans of both groups, bombarding Independentists with violent contents, increasing their exposure to negative and inflammatory narratives, and exacerbating social conflict online. Our findings stress the importance of developing countermeasures to unmask these forms of automated social manipulation.

scholarly journals Exploring Intelligent Approach of Influence Minimization Considering the Node Surveillance in Online Social Networks

2021 ◽  
Author(s):  
JO CHERIYAN ◽  
Sajeev G P
Keyword(s):  
Social Networks ◽  
Energy Level ◽  
Minimization Problem ◽  
Real World ◽  
Online Social Networks ◽  
Information Diffusion ◽  
Multilayer Network ◽  
Influence Propagation ◽  
Awareness Campaigns ◽  
Intelligent Approach

Abstract Attractive information such as innovations, awareness campaigns, branding, and advertising help people positively. Whereas, awful information such as rumors, malicious viruses, pornography, and revenge disturb people. The negative information contributes to chaos among people; therefore, it is to be blocked and hinder from further diffusion. This has motivated us towards the study of the problem named influence minimization. As the real world network can be modeled to a multilayer network, we focus our study towards the information diffusion through a multilayer network. Each node assigns a threshold, and its variation affects the rate of influence propagation across the network. In the influence minimization problem, the energy level of each node changes that help to formulate the function that minimizes the influence propagation. By applying two reduction policies, we are able to optimize our objective of minimizing the influence towards repulsive information. In this article, we consider the user response and its surveillance in the network. Repeated experiments on real networks has helped us to validate the proposed methods.

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