Recent years have witnessed the explosion of online social networks (OSNs). They provide powerful IT-innovations for online social activities such as organizing contacts, publishing contents, and sharing interests between friends who may never meet before. As more and more people become the active users of online social networks, one may ponder questions such as: (1) Do OSNs indeed improve our sociability? (2) To what extent can we expand our offline social spectrum in OSNs? (3) Can we identify some interesting user behaviors in OSNs? Our work in this paper just aims to answer these interesting questions. To this end, we pay a revisit to the well-known Dunbar's number in online social networks. Our main research contributions are as follows. First, to our best knowledge, our work is the first one that systematically validates the existence of the online Dunbar's number in the range of [200,300]. To reach this, we combine using local-structure analysis and user-interaction analysis for extensive real-world OSNs. Second, we divide OSNs users into two categories: rational and aggressive, and find that rational users intend to develop close and reciprocated relationships, whereas aggressive users have no consistent behaviors. Third, we build a simple model to capture the constraints of time and cognition that affect the evolution of online social networks. Finally, we show the potential use of our findings in viral marketing and privacy management in online social networks.
@cite_5: Online social networking sites like Orkut, YouTube, and Flickr are among the most popular sites on the Internet. Users of these sites form a social network, which provides a powerful means of sharing, organizing, and finding content and contacts. The popularity of these sites provides an opportunity to study the characteristics of online social network graphs at large scale. Understanding these graphs is important, both to improve current systems and to design new applications of online social networks. This paper presents a large-scale measurement study and analysis of the structure of multiple online social networks. We examine data gathered from four popular online social networks: Flickr, YouTube, LiveJournal, and Orkut. We crawled the publicly accessible user links on each site, obtaining a large portion of each social network's graph. Our data set contains over 11.3 million users and 328 million links. We believe that this is the first study to examine multiple online social networks at scale. Our results confirm the power-law, small-world, and scale-free properties of online social networks. We observe that the indegree of user nodes tends to match the outdegree; that the networks contain a densely connected core of high-degree nodes; and that this core links small groups of strongly clustered, low-degree nodes at the fringes of the network. Finally, we discuss the implications of these structural properties for the design of social network based systems.
@cite_15: College students spend a significant amount of time using online social net- work services for messaging, sharing information, and keeping in touch with one another (e.g. [3, 10]). As these services represent a plentiful source of electronic data, they provide an opportunity to study dynamic patterns of social interactions quickly and exhaustively. In this paper, we study the social net- work service Facebook, which began in early 2004 in select universities, but grew quickly to encompass a very large number of universities. Studies have shown that, as of 2006, Facebook use is nearly ubiquitous among U. S. college students with over 90 active participation among undergraduates [5, 16].
@cite_16: Social networking services are a fast-growing business in the Internet. However, it is unknown if online relationships and their growth patterns are the same as in real-life social networks. In this paper, we compare the structures of three online social networking services: Cyworld, MySpace, and orkut, each with more than 10 million users, respectively. We have access to complete data of Cyworld's ilchon (friend) relationships and analyze its degree distribution, clustering property, degree correlation, and evolution over time. We also use Cyworld data to evaluate the validity of snowball sampling method, which we use to crawl and obtain partial network topologies of MySpace and orkut. Cyworld, the oldest of the three, demonstrates a changing scaling behavior over time in degree distribution. The latest Cyworld data's degree distribution exhibits a multi-scaling behavior, while those of MySpace and orkut have simple scaling behaviors with different exponents. Very interestingly, each of the two e ponents corresponds to the different segments in Cyworld's degree distribution. Certain online social networking services encourage online activities that cannot be easily copied in real life; we show that they deviate from close-knit online social networks which show a similar degree correlation pattern to real-life social networks.
Recently, researchers have done intensive study in online social networks. They measured the property of online social networks from different perspectives. Phenomena such as small world, power-law, high clustering, assortativity have been observed in different social sites, which are believed to be the common properties of online social networks. studied the largest online social networks Cyworld in South Korea @cite_16 . They experimented on the whole data of Cyworld and discovered some unique characters of this site. They found an interesting phenomenon that most user connections were not active and attributed it to Dunbar's number. used data from Flickr, YouTube, LiveJounal and Orkut, conducting measurement analysis in a large scale @cite_5 . They incorporated various complex network measurements such as degree distribution, clustering coefficients, degree correlations, connected core etc. in the research. analyzed Facebook users in North American colleges or universities @cite_15 . Their results on degree distribution showed that the number of people who have few hundreds of friends remained stable, but it started to drop sharply once the friends number exceeded 250, which also coincided with Dunbar's number.