@article{citeulike:1025135,
  abstract = {A Family of new measures of point and graph centrality based on early intuitions of Bavelas (1948) is introduced. These measures define centrality in terms of the degree to which a point falls on the shortest path between others and therefore has a potential for control of communication. They may be used to index centrality in any large or small network of symmetrical relations, whether connected or unconnected.},
  author = {Freeman, Linton C.},
  citeulike-article-id = {1025135},
  interhash = {7ff13dc1fa197ed99dadeb6e23cf070b},
  intrahash = {05c4b47904e32958af82a2930ef97b3b},
  journal = {Sociometry},
  month = {March},
  number = 1,
  pages = {35--41},
  posted-at = {2007-01-04 16:23:36},
  priority = {2},
  publisher = {American Sociological Association},
  title = {A Set of Measures of Centrality Based on Betweenness},
  url = {http://links.jstor.org/sici?sici=0038-0431\%28197703\%2940\%3A1\%3C35\%3AASOMOC\%3E2.0.CO\%3B2-H},
  volume = 40,
  year = 1977
}

@article{freeman2003fsg,
  author = {Freeman, L.C.},
  booktitle = {Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers},
  interhash = {563243fe694f79b8abfeabe79518918f},
  intrahash = {9d65217331256c63be4712db235af3bf},
  organization = {National Academy Press},
  pages = 39,
  title = {{Finding social groups: A meta-analysis of the southern women data}},
  year = 2003
}

@article{frank1988rsa,
  author = {Frank, O.},
  interhash = {1761045c6709543b29d880bbb0a45cab},
  intrahash = {2d15b32284dc31868096f5220dec0e94},
  journal = {Math. Sci. Humaines},
  pages = {19--33},
  title = {{Random sampling and social networks: a survey of various approaches}},
  volume = 104,
  year = 1988
}

@article{anderson1999ppl,
  author = {Anderson, C.J. and Wasserman, S. and Crouch, B.},
  interhash = {bc2bb58cfd833af662976fa8b73f4607},
  intrahash = {b2e086ec820f42183555e14de772f695},
  journal = {Social Networks},
  number = 1,
  pages = {37--66},
  publisher = {Elsevier},
  title = {{A p* primer: Logit models for social networks}},
  volume = 21,
  year = 1999
}

@article{snijders2002mcm,
  author = {Snijders, T.A.B.},
  interhash = {82953e285fb7bfcc79462f7c38bd8e54},
  intrahash = {b947cc90ef6f010d357c5048389032aa},
  journal = {Journal of Social Structure},
  number = 2,
  pages = {1--40},
  title = {{Markov chain Monte Carlo estimation of exponential random graph models}},
  volume = 3,
  year = 2002
}

@article{cha2007tyt,
  author = {Cha, M. and Kwak, H. and Rodriguez, P. and Ahn, Y.Y. and Moon, S.},
  booktitle = {Proceedings of the 7th ACM SIGCOMM conference on Internet measurement},
  interhash = {d01f4a75a4712049f13c464b31ef6414},
  intrahash = {718bb817f2ee6785831033fe9e4989d0},
  organization = {ACM New York, NY, USA},
  pages = {1--14},
  title = {{I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system}},
  year = 2007
}

@article{keyhere,
  abstract = {Established in 2005, YouTube is one of the fastest-growing websites, and has become one of the most accessed sites in the
Internet. It has a significant impact on the Internet traffic distribution, but itself is suffering from severe scalabilityconstraints. Understanding the features of YouTube and similar video sharing sites is thus crucial to network traffic engineeringand to sustainable development of this new generation of services.},
  author = {Cheng, Xu and Dale, Cameron and Liu, Jiangchuan},
  interhash = {472b1063972e934e1f9ab675b5896a77},
  intrahash = {46d32b77eec4c8ffa4c8f469131a95b1},
  journal = {Peer-to-Peer Video},
  pages = {205--217},
  title = {Characteristics and Potentials of YouTube: A Measurement Study},
  url = {http://dx.doi.org/10.1007/978-0-387-76450-4_9},
  year = 2008
}

@article{gross:ira,
  author = {Gross, R. and Acquisti, A.},
  interhash = {19bb9c028aa5074819b2e2ab1aa90824},
  intrahash = {967d9adc2e573348524ac6dbe09b42fe},
  title = {{Information revelation and privacy in online social networks}},
  year = 2008
}

@inproceedings{1435498,
  address = {New York, NY, USA},
  author = {Maia, Marcelo and Almeida, Jussara and Almeida, Virg\'{\i}lio},
  booktitle = {SocialNets '08: Proceedings of the 1st workshop on Social network systems},
  doi = {http://doi.acm.org/10.1145/1435497.1435498},
  interhash = {c8510afc8df91d8a87bfff0fdacc5cab},
  intrahash = {21aa1a6e2e63cb7c23a29130e69b74af},
  isbn = {978-1-60558-124-8},
  location = {Glasgow, Scotland},
  pages = {1--6},
  publisher = {ACM},
  title = {Identifying user behavior in online social networks},
  url = {http://portal.acm.org/citation.cfm?id=1435497.1435498},
  year = 2008
}

@unpublished{FalBar07,
  author = {Falkowski, Tanja and Barth, Anja},
  interhash = {72bc0bbc724d035ea119f793eb04f636},
  intrahash = {754a48202afdc98227bd53128524a77f},
  note = {Presented at The 4th conference on Applications of Social Network Analysis (ASNA)},
  title = {Density-based Temporal Graph Clustering for Subgroup Detection in Social Networks},
  year = 2007
}

@article{NewmanPark2003aa,
  abstract = {We argue that social networks differ from most other types of networks, including technological and biological networks, in two important ways. First, they have nontrivial clustering or network transitivity and second, they show positive correlations, also called assortative mixing, between the degrees of adjacent vertices. Social networks are often divided into groups or communities, and it has recently been suggested that this division could account for the observed clustering. We demonstrate that group structure in networks can also account for degree correlations. We show using a simple model that we should expect assortative mixing in such networks whenever there is variation in the sizes of the groups and that the predicted level of assortative mixing compares well with that observed in real-world networks.},
  affiliation = {Department of Physics and Center for the Study of Complex Systems, University of Michigan, Ann Arbor, Michigan 48109, USA Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA},
  author = {Newman, M. E. J. and Park, Juyong},
  bdsk-file-1 = {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},
  bdsk-url-1 = {http://link.aps.org/abstract/PRE/v68/e036122},
  date-added = {2008-09-05 14:51:09 -0400},
  date-modified = {2009-07-29 12:55:26 -0400},
  interhash = {c074e9640dd0a12bdcb5165afcab5981},
  intrahash = {50b704e757d57dea99993270246510a4},
  journal = {Phys. Rev. E},
  language = {eng},
  month = sep,
  number = 3,
  pages = 036122,
  rating = {0},
  title = {Why Social Networks Are Different from Other Types of Networks},
  uri = {papers://4845910D-5DD6-40DD-88AD-7D11EF9A6B0A/Paper/p617},
  volume = 68,
  year = 2003
}

@article{schifanella2010folks,
  author = {Schifanella, R. and Barrat, A. and Cattuto, C. and Markines, B. and Menczer, F.},
  interhash = {4af819bc8d669b827b8e50017fcb1744},
  intrahash = {5fd8eceb8d057d1379f862613937a2d7},
  title = {{Folks in folksonomies: Social link prediction from shared metadata}},
  url = {http://scholar.google.de/scholar.bib?q=info:5fwGHbzyqVgJ:scholar.google.com/&output=citation&hl=de&as_sdt=2000&ct=citation&cd=0},
  year = 2010
}

@article{mislove2007measurement,
  author = {Mislove, A. and Marcon, M. and Gummadi, K.P. and Druschel, P. and Bhattacharjee, B.},
  booktitle = {Proceedings of the 7th ACM SIGCOMM conference on Internet measurement},
  interhash = {cb29c839ea0b125778ae58934f35082f},
  intrahash = {aa568938d581a2885e7898e4852ee62f},
  organization = {ACM},
  pages = 42,
  title = {{Measurement and analysis of online social networks}},
  url = {http://scholar.google.de/scholar.bib?q=info:HmucgVkM3hQJ:scholar.google.com/&output=citation&hl=de&as_sdt=2000&ct=citation&cd=0},
  year = 2007
}

@inproceedings{1150476,
  abstract = {In this paper, we consider the evolution of structure within large online social networks. We present a series of measurements of two such networks, together comprising in excess of five million people and ten million friendship links, annotated with metadata capturing the time of every event in the life of the network. Our measurements expose a surprising segmentation of these networks into three regions: singletons who do not participate in the network; isolated communities which overwhelmingly display star structure; and a giant component anchored by a well-connected core region which persists even in the absence of stars.We present a simple model of network growth which captures these aspects of component structure. The model follows our experimental results, characterizing users as either passive members of the network; inviters who encourage offline friends and acquaintances to migrate online; and linkers who fully participate in the social evolution of the network.},
  address = {New York, NY, USA},
  author = {Kumar, Ravi and Novak, Jasmine and Tomkins, Andrew},
  booktitle = {KDD '06: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining},
  doi = {http://doi.acm.org/10.1145/1150402.1150476},
  interhash = {d3729a29d377e03b31c80bcc58843681},
  intrahash = {03874e666c56f22bce1b7db254420d77},
  isbn = {1-59593-339-5},
  location = {Philadelphia, PA, USA},
  pages = {611--617},
  publisher = {ACM},
  title = {Structure and evolution of online social networks},
  url = {http://portal.acm.org/citation.cfm?id=1150402.1150476},
  year = 2006
}

@inproceedings{citeulike:5980713,
  abstract = {Many Web users have accounts with multiple different social networking services. This scenario has prompted development of "social aggregation" services such as FriendFeed that aggregate the information available through various services. Using five weeks of activity of more than 100,000 FriendFeed users, we consider questions such as what types of services users aggregate content from, the relative popularity of services, who follows the aggregated content feeds, and why.},
  author = {Gupta, T. and Garg, S. and Mahanti, A. and Carlsson, N. and Arlitt, M.},
  citeulike-article-id = {5980713},
  citeulike-linkout-0 = {http://www.aaai.org/ocs/index.php/ICWSM/09/paper/view/193},
  interhash = {9452ec7c732ebad7d2814935ecf3d78c},
  intrahash = {8d41f015e4e1523bede220dbed946f56},
  journal = {International AAAI Conference on Weblogs and Social Media},
  month = {March},
  posted-at = {2009-10-21 17:10:15},
  priority = {0},
  title = {Characterization of FriendFeed - A Web-based Social Aggregation Service},
  url = {http://www.aaai.org/ocs/index.php/ICWSM/09/paper/view/193},
  year = 2009
}

@article{newman2003social,
  author = {Newman, MEJ and Park, J.},
  interhash = {c074e9640dd0a12bdcb5165afcab5981},
  intrahash = {63485bb49644f266dec9a4fddf447fb9},
  journal = {Physical Review E},
  number = 3,
  pages = 36122,
  publisher = {APS},
  title = {{Why social networks are different from other types of networks}},
  url = {http://scholar.google.de/scholar.bib?q=info:Ep_ADiiiopYJ:scholar.google.com/&output=citation&hl=de&as_sdt=2000&ct=citation&cd=0},
  volume = 68,
  year = 2003
}

@book{BraErl05,
  author = {Brandes, Ulrik and Erlebach, Thomas},
  interhash = {063c95923f07b0180d16336ef0c8ac56},
  intrahash = {ab8b0742de22b0fa06206089d52883da},
  publisher = {Springer},
  title = {Network Analysis: Methodological Foundations},
  year = 2005
}

@inproceedings{mitzlaff2010visit,
  address = {Toronto, Canada},
  author = {Mitzlaff, Folke and Benz, Dominik and Stumme, Gerd and Hotho, Andreas},
  booktitle = {Proceedings of the 21st ACM conference on Hypertext and hypermedia},
  interhash = {5584c4c57fcd8eb4663df8b114bcf09c},
  intrahash = {a97c4f7e80dcb666450acf697002155e},
  note = {(to appear)},
  title = {Visit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy},
  year = 2010
}