@inproceedings{kibanov2013evolution,
  address = {Boston, MA, USA},
  author = {Kibanov, Mark and Atzmueller, Martin and Scholz, Christoph and Stumme, Gerd},
  booktitle = {Proc. IEEE CPSCom 2013},
  interhash = {14e73d96c8554e73214c36b49add934c},
  intrahash = {5824b6151b2046d6295e4300311b7e8e},
  publisher = {IEEE Computer Society},
  title = {{On the Evolution of Contacts and Communities in Networks of Face-to-Face Proximity}},
  year = 2013
}

@inproceedings{Backstrom:2007:WAT:1242572.1242598,
  abstract = {In a social network, nodes correspond topeople or other social entities, and edges correspond to social links between them. In an effort to preserve privacy, the practice of anonymization replaces names with meaningless unique identifiers. We describe a family of attacks such that even from a single anonymized copy of a social network, it is possible for an adversary to learn whether edges exist or not between specific targeted pairs of nodes.},
  acmid = {1242598},
  address = {New York, NY, USA},
  author = {Backstrom, Lars and Dwork, Cynthia and Kleinberg, Jon},
  booktitle = {Proceedings of the 16th international conference on World Wide Web},
  doi = {10.1145/1242572.1242598},
  interhash = {aa7d0f96c372d2c03d228f27a7f4b66b},
  intrahash = {913059fcbf0453c60ff8b79e2705742c},
  isbn = {978-1-59593-654-7},
  location = {Banff, Alberta, Canada},
  numpages = {10},
  pages = {181--190},
  publisher = {ACM},
  series = {WWW '07},
  title = {Wherefore art thou r3579x?: anonymized social networks, hidden patterns, and structural steganography},
  url = {http://doi.acm.org/10.1145/1242572.1242598},
  year = 2007
}

@misc{Narayanan2009,
  abstract = {  Operators of online social networks are increasingly sharing potentially
sensitive information about users and their relationships with advertisers,
application developers, and data-mining researchers. Privacy is typically
protected by anonymization, i.e., removing names, addresses, etc.
  We present a framework for analyzing privacy and anonymity in social networks
and develop a new re-identification algorithm targeting anonymized
social-network graphs. To demonstrate its effectiveness on real-world networks,
we show that a third of the users who can be verified to have accounts on both
Twitter, a popular microblogging service, and Flickr, an online photo-sharing
site, can be re-identified in the anonymous Twitter graph with only a 12% error
rate.
  Our de-anonymization algorithm is based purely on the network topology, does
not require creation of a large number of dummy "sybil" nodes, is robust to
noise and all existing defenses, and works even when the overlap between the
target network and the adversary's auxiliary information is small.
},
  author = {Narayanan, Arvind and Shmatikov, Vitaly},
  interhash = {ffb21f5ed2b9b879d911d0b68f3d5c07},
  intrahash = {396299d0adaba60baa0f4c2bd28a93b8},
  note = {cite arxiv:0903.3276
Comment: Published in the 30th IEEE Symposium on Security and Privacy, 2009.
  The definitive version is available at:
  http://www.cs.utexas.edu/~shmat/shmat_oak09.pdf Frequently Asked Questions
  are answered at: http://www.cs.utexas.edu/~shmat/socialnetworks-faq.html},
  title = {De-anonymizing Social Networks},
  url = {http://arxiv.org/abs/0903.3276},
  year = 2009
}

@inproceedings{das2008efficient,
  abstract = {As online social networking emerges, there has been increased interest to utilize the underlying social structure as well as the available social information to improve search. In this paper, we focus on improving the performance of information collection from the neighborhood of a user in a dynamic social network. To this end, we introduce sampling based algorithms to quickly approximate quantities of interest from the vicinity of a user's social graph. We then introduce and analyze variants of this basic scheme exploring correlations across our samples. Models of centralized and distributed social networks are considered. We show that our algorithms can be utilized to rank items in the neighborhood of a user, assuming that information for each user in the network is available. Using real and synthetic data sets, we validate the results of our analysis and demonstrate the efficiency of our algorithms in approximating quantities of interest. The methods we describe are general and can probably be easily adopted in a variety of strategies aiming to efficiently collect information from a social graph.},
  address = {New York, NY, USA},
  author = {Das, Gautam and Koudas, Nick and Papagelis, Manos and Puttaswamy, Sushruth},
  booktitle = {SSM '08: Proceeding of the 2008 ACM workshop on Search in social media},
  doi = {http://doi.acm.org/10.1145/1458583.1458594},
  interhash = {8f5b97910a5d3c0c7ed427309aae9fd7},
  intrahash = {64b5d84df9aacd4c2956d4780ddc98c2},
  isbn = {978-1-60558-258-0},
  location = {Napa Valley, California, USA},
  pages = {67--74},
  publisher = {ACM},
  title = {Efficient sampling of information in social networks},
  url = {http://portal.acm.org/citation.cfm?id=1458583.1458594},
  year = 2008
}

@inproceedings{1526808,
  abstract = {In this paper we give models and algorithms to describe and analyze the collaboration among authors of Wikipedia from a network analytical perspective. The edit network encodes who interacts how with whom when editing an article; it significantly extends previous network models that code author communities in Wikipedia. Several characteristics summarizing some aspects of the organization process and allowing the analyst to identify certain types of authors can be obtained from the edit network. Moreover, we propose several indicators characterizing the global network structure and methods to visualize edit networks. It is shown that the structural network indicators are correlated with quality labels of the associated Wikipedia articles.},
  address = {New York, NY, USA},
  author = {Brandes, Ulrik and Kenis, Patrick and Lerner, J\"{u}rgen and van Raaij, Denise},
  booktitle = {WWW '09: Proceedings of the 18th international conference on World wide web},
  doi = {http://doi.acm.org/10.1145/1526709.1526808},
  interhash = {1d0c41c49ae3821dbde05fe6e34d0a4a},
  intrahash = {3569586bacbec77f6da6db5461db7857},
  isbn = {978-1-60558-487-4},
  location = {Madrid, Spain},
  pages = {731--740},
  publisher = {ACM},
  title = {Network analysis of collaboration structure in Wikipedia},
  url = {http://portal.acm.org/citation.cfm?id=1526808},
  year = 2009
}

@inproceedings{1367620,
  abstract = {We present a study of anonymized data capturing a month of high-level communication activities within the whole of the Microsoft Messenger instant-messaging system. We examine characteristics and patterns that emerge from the collective dynamics of large numbers of people, rather than the actions and characteristics of individuals. The dataset contains summary properties of 30 billion conversations among 240 million people. From the data, we construct a communication graph with 180 million nodes and 1.3 billion undirected edges, creating the largest social network constructed and analyzed to date. We report on multiple aspects of the dataset and synthesized graph. We find that the graph is well-connected and robust to node removal. We investigate on a planetary-scale the oft-cited report that people are separated by "six degrees of separation" and find that the average path length among Messenger users is 6.6. We find that people tend to communicate more with each other when they have similar age, language, and location, and that cross-gender conversations are both more frequent and of longer duration than conversations with the same gender.},
  address = {New York, NY, USA},
  author = {Leskovec, Jure and Horvitz, Eric},
  booktitle = {WWW '08: Proceeding of the 17th international conference on World Wide Web},
  doi = {http://doi.acm.org/10.1145/1367497.1367620},
  interhash = {27d7144813bb85492b18cad6cf6525e7},
  intrahash = {bfe758ce74fac01c2108c3f2184d6c48},
  isbn = {978-1-60558-085-2},
  location = {Beijing, China},
  pages = {915--924},
  publisher = {ACM},
  title = {Planetary-scale views on a large instant-messaging network},
  url = {http://portal.acm.org/citation.cfm?id=1367620},
  year = 2008
}

@inproceedings{paper:lambiotte:2006,
  abstract = {We describe online collaborative communities by tripartite networks, the nodes being persons, items and tags. We introduce projection methods in order to uncover the structures of the networks, i.e. communities of users, genre families... The structuring of the network is visualised by using a tree representation. The notion of diversity in the system is also discussed.},
  author = {Lambiotte, Renaud and Ausloos, Marcel},
  booktitle = {Computational Science – ICCS 2006},
  interhash = {1ed3cd51137e724355234662fac3bdda},
  intrahash = {71f0fcb3b9b1cbe601da92fd3bf7ce60},
  pages = {1114-1117},
  publisher = {Springer Berlin / Heidelberg},
  title = {Collaborative Tagging as a Tripartite Network},
  year = 2006
}

@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
}

@book{Scott:2005,
  abstract = {Literaturverz. S. [193] - 204},
  author = {Scott, John},
  interhash = {fccce2e9a2ce1ad36eba7838b6fe9ae3},
  intrahash = {a1419b1e02fd01a2b0f6e048084237f8},
  isbn = {0-7619-6338-3},
  opac = {http://opac.bibliothek.uni-kassel.de/DB=23/PPN?PPN=128222697},
  publisher = {Sage Publ. London [u.a.]},
  title = {Social network analysis},
  url = {http://opac.bibliothek.uni-kassel.de/DB=23/PPN?PPN=128222697},
  year = 2005
}

@book{Carrington:2007,
  abstract = {Literaturangaben},
  author = {Carrington, Peter J.},
  interhash = {8d216af7fe707e3f7b4f9ba2f1d2835b},
  intrahash = {3c9f0a91bbacb78af8960b06401ccfcb},
  isbn = {0-521-80959-2},
  opac = {http://opac.bibliothek.uni-kassel.de/DB=23/PPN?PPN=190999837},
  publisher = {Cambridge Univ. Press Cambridge [u.a.]},
  series = {Structural analysis in the social sciences},
  title = {Models and methods in social network analysis},
  url = {http://opac.bibliothek.uni-kassel.de/DB=23/PPN?PPN=190999837},
  year = 2007
}

@article{batagelj2009social,
  author = {BATAGELJ, VLADIMIR},
  interhash = {3a98587c6e23fea6662f78ea02d4ff87},
  intrahash = {1a58279d325463798683c9d281da2776},
  journal = {Encyclopedia of Complexity and System Science},
  title = {Social Network Analysis, Large-scale},
  url = {http://vlado.fmf.uni-lj.si/pub/networks/doc/mix/LargeSNA.pdf},
  year = 2009
}

@inproceedings{freeman03finding,
  author = {Freeman, Linton C.},
  booktitle = {Dynamic Social Network Modeling and Analysis:  Workshop Summary and Papers},
  editor = {Breiger, Ronald and Carley, Kathleen and Pattison, Philippa},
  interhash = {563243fe694f79b8abfeabe79518918f},
  intrahash = {02e65fb29949598a0b80746df62d34e3},
  publisher = {National Academies Press},
  title = {Finding Social Groups: A Meta-Analysis of the Southern Women Data},
  year = 2003
}

@inproceedings{Brandes07Role,
  abstract = {Abstract. Communities in social networks are often defined as groups of densely connected actors. However, members of the same dense group are not equal but may differ largely in their social position or in the role they play. Furthermore, the same positions can be found across the borders of dense communities so that networks contain a significant group
structure which does not coincide with the structure of dense groups.
This papers gives a survey over formalizations of network-positions with a special emphasis on the use of algebraic notions.},
  author = {Brandes, Ulrik and Lerner, Jürgen},
  booktitle = {ICFCA 2007 Satellite Workshop on Social Network Analysis and Conceptual Structures: Exploring Opportunities},
  editor = {Obiedkov, Sergei and Roth, Camille},
  interhash = {38a2ada146d754d86889068e548316ec},
  intrahash = {6ea541158f972b850e9ea330b473c7c4},
  title = {Role-equivalent Actors in Networks},
  url = {http://www.inf.uni-konstanz.de/algo/publications/bl-rean-07.pdf},
  year = 2007
}

@article{white1996social,
  author = {White, D. and Duquenne, V.},
  booktitle = {Social Network and Discrete Structure Analysis},
  interhash = {12a0e0bb0653928d656430a22367b57b},
  intrahash = {54623418afefedc61bb05f69a8245506},
  journal = {Social Networks},
  month = {#aug#},
  number = 3,
  pages = {169--172},
  title = {Introduction},
  url = {http://www.sciencedirect.com/science/article/B6VD1-48DY2VM-1/2/effdb898eb0e033668f4e2be4ca41d5c},
  volume = 18,
  year = 1996
}

@article{baerveldt1994influences,
  author = {Baerveldt, T. A. B.},
  interhash = {e341edae7edaaa4da9dd044b943912a2},
  intrahash = {0d6b995d6befb04a68aa8638d69887d8},
  journal = { Social Networks},
  pages = {213-232},
  title = {Influences on and from the segmentation of networks: hypotheses and tests},
  url = {http://www.prevention.psu.edu/events/documents/BaerveldtandSnijders1994_Influencesonandfromthesegmentation.pdf},
  volume = 16,
  year = 1994
}