Online social network

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Online social network

  1. 1. GUEST EDITORIALOnline Social Networks Michalis Faloutsos Thomas Karagiannis Sue MoonT he popularity and complexity of online social net- works (OSNs) continues to grow unabatedly with the most popular applications featuring hundreds of mil-lions of active users. Ranging from social communities anddiscussion groups, to recommendation engines, tagging sys- • User activity: What are the characteristics of user online time in popular OSNs? • Population of online services: How can we model, describe, and sample OSNs when they are dynamic and large, and obtaining a complete snapshot is often impos-tems, mobile social networks, games, and virtual worlds, sible?OSN applications have not only shifted the focus of appli- • Profile characterization: How do people use OSNs, cancation developers to the human factor, but have also trans- we reverse engineer behavior, and can we identify pro-formed traditional application paradigms such as the way files based, say, on gender?users communicate and navigate in the Internet. Indeed, In the first article of this issue, Yang et al. explore theunderstanding user behavior is now an integral part of problem of modeling human mobility by exploiting under-online services and applications, with system and algorithm lying social norms. The authors’ key insight is that individu-design becoming in effect user-centric. As expected, this al people’s movements depend on their social interactions;paradigm shift has not left the research community unaf- as a result, the social network consists of overlapping com-fected, triggering intense research interest in the analysis of munities. However, instead of forming or detecting com-the structure and properties of online communities. munities in generated graphs, the authors propose a While the first phase of OSN research heavily focused bottom-up approach by first forming individual communi-on characterizing the properties of the social graph, cur- ties, and then establishing their overlapping structure. Byrently, the research community has shown an increased comparing the proposed model with real traces of humaninterest in how basic properties of social network theory mobility, the authors show that their model can approxi-can 1) explain observed online human behavior and 2) be mate properties such as the inter-contact time or degreeexploited to drive the design of algorithms and large-scale distributions, arguing that social structures play a signifi-distributed systems. Indeed, this second phase of OSN cant role in human mobility.research is also reflected in the current special issue of The potential of exploiting large-scale OSN services forIEEE Network. The special issue features an ensemble of malicious activities is the subject of the article by Makri-interesting articles demonstrating the breadth and variety dakis et al. The authors show how the widespread growth ofof OSN applications, such as location-based social network such services, the underlying trust they establish amongservices, security and privacy of OSNs, and human mobility users, and their “open platform” architecture are the idealmodels based on social network theory. properties for turning OSNs into new vectors of attack.In particular, this special issue attempts to provide insights The authors expose the feasibility of converting Facebookwith respect to the following questions: applications to denial of service platforms, demonstrate• Human mobility: Could social network theory explain how to retrieve remote files from a user’s machine, and properties of human mobility, and, if so, which of these expose potential leakage of private information despite the properties can be replicated in the proposed models? relevant privacy settings. Overall, the article provides sim-• Security: Following the abuse of email and websites, can ple proof-of-concept examples of misuses in popular OSNs, OSNs be used as a new vector of attack to propagate and stresses the importance of advanced protection mecha- malware and compromise user machines? nisms tailored to these services.• Privacy: How do users perceive their privacy in location- The article by Li et al. further explores how users per- based social network services? ceive privacy but in a different context. Specifically, shar-4 IEEE Network • September/October 2010
  2. 2. GUEST EDITORIALing location information is an important feature of OSNs and blog content. The study highlights how commercialthat is gaining increasing attention among OSN users. profiles, whose particular aim is to attract users, featureLocation-based OSNs, or “LSNs,” as referred to by the unique properties from those of individual user profiles.authors, are explored in the third article of this special Concluding this editorial, we would like to thank theissue. The article provides a brief description of some pop- Editor-in-Chief, Tom Chen, for his valuable support andular services in the space, summarizes their features, and guidance throughout this special issue. We are also gratefulexamines how private information might be exposed in to all the reviewers whose efforts and comments made thissuch services. The authors study how privacy concerns special issue possible.depend on different users groups, user ages, access meth-ods, or geographical regions. Biographies The characterization of user online activity in several MICHALIS FALOUTSOS (michalis@cs.ucr.edu) is a faculty member in the Computerpopular OSNs is the subject of a study by Gyarmati et al. Science Department at the University of California, Riverside. He got his Bache-The study uses PlanetLab as a measurement infrastructure lor’s degree from the National Technical University of Athens, and his M.Sc and Ph.D. from the University of Toronto. His interests include Internet protocols and mea-monitoring thousands of user profiles for BeBo, MySpace, surements, network security, and routing in ad hoc networks. With his twoNetlog, and Tagged. The article characterizes access pat- brothers, he co-authored the paper “On Power Laws of the Internet Topology”terns of users in these OSNs, covering aspects related to (SIGCOMM’99), which received the “Test of Time” award from ACM SIG- COMM. His work has been supported by several NSF and DAPRA grants,the user online time, duration of user sessions, and user including the prestigious NSF CAREER award with a cumulative of more than $5activity time. The authors perform a statistical analysis of million in grants. He has been authoring the popular column “You Must Be Jok- ing...” in ACM SIGCOMM Computer Communication Review , which reachesthe distributions of specific properties, and expose the fact 9000 downloads. He is the co-founder of stopthehacker.com, a web securitythat attracting the interest of users who have recently startup.joined an OSN may not be trivial. THOMAS KARAGIANNIS (thomkar@microsoft.com) is a researcher with the Systems The fraction of active and “non-active” users and the and Networking group of Microsoft Research Cambridge, United Kingdom. Hesize of OSNs is under study also in the article by Rejaie et received his Ph.D. in computer science from the University of California, River-al. The authors devise strategies to estimate the number of side and his B.S from the Applied Informatics Department of the University of Macedonia, Thessaloniki, Greece. Before joining Microsoft, he was with Intel Researchusers for MySpace and Twitter by exploiting information and the Cooperative Association for Internet Data Analysis (CAIDA). He hasabout the allocation of numeric user IDs. By inferring this served as a chair and steering committee member for the Workshop on Online Social Networks (WOSN), and as a TPC member for several conferences such as SIG-allocation strategy, the authors can estimate the total popu- COMM, IMC, and INFOCOM. His research interests include Internet measure-lation of users at the time a user joined. The authors fur- ments and modeling, analysis and characterization of the traffic of Internet applications,ther present information regarding the number of deleted and peer-to-peer and social networks.accounts and their corresponding lifespans. Overall, the SUE MOON (sbmoon@kaist.edu) received her B.S. and M.S. from Seoul Nationalstudy reports that the active population of these OSNs is an University, Korea, in 1988 and 1990, respectively, both in computer engineer-order of magnitude smaller than their reported population ing. She received a Ph.D. degree in computer science from the University of Massachusetts at Amherst in 2000. From 1999 to 2003 she worked in thesizes. IPMON project at Sprint ATL, Burlingame, California. In August 2003 she Finally, Gauvin et al. study how user profile characteris- joined KAIST and now teaches in Daejeon, Korea. She has served as TPC co- chair for ACM Multimedia and ACM SIGCOMM MobiArch Workshop, generaltics depend on user gender in MySpace. The authors chair for PAM, and TPC for many conferences, including SIGCOMM 2010,explore several properties such as the effect of user age, NSDI 2008 and 2010, WWW 2007–2008, INFOCOM 2004–2006, and IMCthe correlation between the number of friends and number 2009. She won the best paper award at ACM SIGCOMM Internet Measurement Conference 2007 and was awarded the Amore Pacific Woman Scientist Awardof publishers (e.g., friends that publish on a user’s wall), in 2009. Her research interests are: network performance measurement andage similarity between interacting users, temporal patterns, analysis, online social networks, and networked systems.IEEE Network • September/October 2010 5

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