Analysis of topological characteristics of huge online social networking services

By Yong-Yeol Ahn, Seungyeop Han, Haewoon Kwak, Sue B. Moon, Hawoong Jeong. The Web Conference, 2007

1,050 citations recorded by the source corpus.

Subfields: Statistical and Nonlinear Physics, Transportation

View Paper: https://www.semanticscholar.org/paper/bff18349e79056743d7b68a0b8b5fb21e9b720a8

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In Statistical and Nonlinear Physics

In Transportation

Citations in the corpus

Comparison of online social relations in volume vs interaction: a case study of cyworld (2008, methodology): “It is concurrent to our knowledge that the online relationship seems to be more shallow and easy to be formed [2].”
Evolution of social-attribute networks: measurements, modeling, and implications using google+ (2012, background): “Most prior work in the measurement and modeling space focuses primarily on the social structure [3, 4, 13, 26, 28, 33, 38].”
Patterns and dynamics of users' behavior and interaction: Network analysis of an online community (2009, methodology): “However, because, in our case, the system follows a non-linear process of “accelerated” growth, the structure of ties becomes denser over time, and thus average separation between users decreases (Ahn et al., 2007; Barabási et al., 2002; Holme et al., 2004; Leskovec, Kleinberg, & Faloutsos, 2005).”
#mytweet via Instagram: Exploring user behaviour across multiple social networks (2015, methodology): “Leveraging the user relationship graph, early studies [1], [2] investigated the structural properties among networks such as Flickr, YouTube and Myspace.”
The tube over time: characterizing popularity growth of youtube videos (2011, methodology): “Categories and Subject Descriptors C.4 [Computer Systems Organization]: Performance of Systems Measurement techniques; H.3.5 [Information Storage and Retrieval]: Online Information Services Web-based services General Terms Human Factors, Measurement Permission to make digital or hard copies of…”
Man vs. Machine: Practical Adversarial Detection of Malicious Crowdsourcing Workers (2014, background): “4Snowball crawls start from an initial set of seed nodes, and r u s breadth-first search to find all reachable nodes in the social graph [3].”
On the evolution of user interaction in Facebook (2009, background): “Recently, much work has focused on understanding the structure and evolution of large-scale online social networks [1,10,11].”
What is Twitter, a social network or a news media? (2010, methodology): “Similar tail behavior in degree distribution has been reported from Cyworld in [1] but not from other social networks.”
Walking in Facebook: A Case Study of Unbiased Sampling of OSNs (2010, methodology): “First, we consider Breadth-First-Search (BFS) - the heretofore most widely used technique for measurements of OSNs [5], [6] and FB [7].”
Event-based social networks: linking the online and offline social worlds (2012, background): “The online social network [1, 18] or the offline social network [2, 22] alone is not new and has been studied extensively before.”
Understanding latent interactions in online social networks (2010, background): “2009], Cyworld [Ahn et al. 2007], and Orkut [Mislove et al.”
When Social Influence Meets Item Inference (2015, background): “to the emergence of massive data in varied applications. Breadth-First-Search (BFS) and Random Walk (RW) (and its variations) have been adopted by many crawlers to generate released datasets for OSNs [8, 24], Web [15], P2P networks [27], and other types of graphs [19]. However, BFS and RW tend to in”
The Anatomy of the Facebook Social Graph (2011, background): “360, Cyworld, Myspace, Orkut, and LiveJournal among others [7–11].”
Measurement and analysis of online social networks (2007, methodology): “have generally relied on propreitary data obtained from the operators of a single large network [4].”
Characterizing user behavior in online social networks (2009, background): “[1] studied the network properties of Cyworld, a popular OSN in South Korea.”
Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, background): “While most web sites simply disappear during the years, Cyworld is an example of successful online social environment, providing a network of more than 12 million nodes [292].”