@inproceedings{scholz2013people, author = {Scholz, Christoph and Atzmueller, Martin and Kibanov, Mark and Stumme, Gerd}, booktitle = {ASONAM}, interhash = {8b6051b794789000c4baa5ab059fab18}, intrahash = {bf958ff2b11df1d9d15d9287ea07a5c9}, title = {How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks}, year = 2013 } @inproceedings{scholz2013people, abstract = {Understanding the process of link creation is rather important for link prediction in social networks. Therefore, this paper analyzes contact structures in networks of face-to-face spatial proximity, and presents new insights on the dynamic and static contact behavior in such real world networks. We focus on face-to-face contact networks collected at different conferences using the social conference guidance system Conferator. Specifically, we investigate the strength of ties and its connection to triadic closures in face-to-face proximity networks. Furthermore, we analyze the predictability of all, new and recurring links at different points of time during the conference. In addition, we consider network dynamics for the prediction of new links.}, address = {Los Alamitos, CA, USA}, author = {Scholz, Christoph and Atzmueller, Martin and Kibanov, Mark and Stumme, Gerd}, booktitle = {Advances in Social Networks Analysis and Mining (ASONAM), 2013 International Conference on}, interhash = {8b6051b794789000c4baa5ab059fab18}, intrahash = {15cbb7f4dbbb8bc6ee9b7a2bf666f032}, title = {How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks}, year = 2013 } @incollection{atzmueller2013social, address = {Heidelberg, Germany}, author = {Atzmueller, Martin}, booktitle = {Mobile Social Networking: An Innovative Approach}, editor = {Chin, Alvin and Zhang, Daqing}, interhash = {1be75b604acbaf39653eeca9833782df}, intrahash = {cd910f3a16c9368e7b73407708452653}, publisher = {Springer Verlag}, title = {{Social Behavior in Mobile Social Networks: Characterizing Links, Roles and Communities}}, year = 2013 } @article{Atzmueller:12c, author = {Atzmueller, Martin}, interhash = {0b20c1d53d5df05326d594726273c2fb}, intrahash = {7b616e64994893a2aad95b5ad95db662}, journal = {WIREs: Data Mining and Knowledge Discovery}, title = {{Mining Social Media: Key Players, Sentiments, and Communities}}, volume = {In Press}, year = 2012 } @article{berendt2010bridging, author = {Berendt, Bettina and Hotho, Andreas and Stumme, Gerd}, doi = {DOI: 10.1016/j.websem.2010.04.008}, interhash = {4969eb2b7bf1fabe60c5f23ab6383d77}, intrahash = {f8d7bc2af5753906dc3897196daac18c}, issn = {1570-8268}, journal = {Web Semantics: Science, Services and Agents on the World Wide Web}, note = {Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0; The Future of Knowledge Dissemination: The Elsevier Grand Challenge for the Life Sciences}, number = {2-3}, pages = {95 - 96}, title = {Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0}, url = {http://www.sciencedirect.com/science/article/B758F-4YXK4HW-1/2/4cb514565477c54160b5e6eb716c32d7}, volume = 8, year = 2010 } @inproceedings{krause2008logsonomy, abstract = {Social bookmarking systems constitute an established part of the Web 2.0. In such systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Today’s search engines represent the gateway to retrieve information from the World Wide Web. Short queries typically consisting of two to three words describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. This clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large snapshot of del.icio.us and on query logs of two large search engines. All of the three datasets show small world properties. The tagging behavior of users, which is explained by preferential attachment of the tags in social bookmark systems, is reflected in the distribution of single query words in search engines. We can conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics.}, address = {New York, NY, USA}, author = {Krause, Beate and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd}, booktitle = {HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia}, doi = {http://doi.acm.org/10.1145/1379092.1379123}, interhash = {6d34ea1823d95b9dbf37d4db4d125d2a}, intrahash = {e64d14f3207766f4afc65983fa759ffe}, isbn = {978-1-59593-985-2}, location = {Pittsburgh, PA, USA}, pages = {157--166}, publisher = {ACM}, title = {Logsonomy - Social Information Retrieval with Logdata}, url = {http://portal.acm.org/citation.cfm?id=1379092.1379123&coll=ACM&dl=ACM&type=series&idx=SERIES399&part=series&WantType=Journals&title=Proceedings%20of%20the%20nineteenth%20ACM%20conference%20on%20Hypertext%20and%20hypermedia}, vgwort = {17}, year = 2008 } @inproceedings{breslin2009integrating, abstract = {Sensors have begun to infiltrate people's everyday lives. They can provide information about a car's condition, can enable smart buildings, and are being used in various mobile applications, to name a few. Generally, sensors provide information about various aspects of the real world. Online social networks, another emerging trend over the past six or seven years, can provide insights into the communication links and patterns between people. They have enabled novel developments in communications as well as transforming the Web from a technical infrastructure to a social platform, very much along the lines of the original Web as proposed by Tim Berners-Lee, which is now often referred to as the Social Web. In this position paper, we highlight some of the interesting research areas where sensors and social networks can fruitfully interface, from sensors providing contextual information in context-aware and personalized social applications, to using social networks as "storage infrastructures" for sensor information.}, author = {Breslin, John G. and Decker, Stefan and Hauswirth, Manfred and Hynes, Gearoid and Phuoc, Danh Le and Passant, Alexandre and Polleres, Axel and Rabsch, Cornelius and Reynolds, Vinny}, booktitle = {Proceedings on the W3C Workshop on the Future of Social Networking}, interhash = {8a9846d06fcb3d48e5f081801a957565}, intrahash = {e5286c49f4a49bb8752d473f126824dd}, title = {Integrating Social Networks and Sensor Networks}, url = {http://www.w3.org/2008/09/msnws/papers/sensors.html}, year = 2009 } @proceedings{alani2006proceedings, editor = {Alani, Harith and Hoser, Bettina and Schmitz, Christoph and Stumme, Gerd}, interhash = {e991143409a8f4acb9eabfe08a38e387}, intrahash = {786a452a14c5189d82dc56f16cc2a266}, title = {Proceedings of the 2nd Workshop on Semantic Network Analysis}, url = {http://www.kde.cs.uni-kassel.de/ws/sna2006/}, year = 2006 } @inproceedings{schmitz2006mining, abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.}, address = {Heidelberg}, author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd}, booktitle = {Data Science and Classification. Proceedings of the 10th IFCS Conf.}, editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and Žiberna, A.}, interhash = {20650d852ca3b82523fcd8b63e7c12d7}, intrahash = {11b2a59a568d246d7f36cb68169a464a}, month = {July}, pages = {261--270}, publisher = {Springer}, series = {Studies in Classification, Data Analysis, and Knowledge Organization}, title = {Mining Association Rules in Folksonomies}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006mining.pdf}, year = 2006 } @proceedings{stumme05semanticnetworkanalysis, address = {Aachen}, editor = {Stumme, Gerd and Hoser, Bettina and Schmitz, Christoph and Alani, Harith}, interhash = {6316cb226778a6a6f156821f975b2ba3}, intrahash = {c44763991d44182c53606a2c93054f26}, issn = {1613-0073}, publisher = {CEUR Proceedings}, title = {Proceedings of the First Workshop on Semantic Network Analysis }, url = {http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-171/}, year = 2005 } @article{cattuto2007network, author = {Cattuto, Ciro and Schmitz, Christoph and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio and Hotho, Andreas and Grahl, Miranda and Stumme, Gerd}, editor = {Hoche, Susanne and Nürnberger, Andreas and Flach, Jürgen}, interhash = {fc5f2df61d28bc99b7e15029da125588}, intrahash = {da6c676c5664017247c7564fc247b190}, issn = {0921-7126}, journal = {AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering''}, number = 4, pages = {245-262}, publisher = {IOS Press}, title = {Network Properties of Folksonomies}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2007/cattuto2007network.pdf}, vgwort = {67}, volume = 20, year = 2007 } @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 } @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 } @misc{noack08modularity, abstract = { Two natural and widely used representations for the community structure of networks are clusterings, which partition the vertex set into disjoint subsets, and layouts, which assign the vertices to positions in a metric space. This paper unifies prominent characterizations of layout quality and clustering quality, by showing that energy models of pairwise attraction and repulsion subsume Newman and Girvan's modularity measure. Layouts with optimal energy are relaxations of, and are thus consistent with, clusterings with optimal modularity, which is of practical relevance because both representations are complementary and often used together.}, author = {Noack, Andreas}, interhash = {a2442ee608964a82be06224fd90d54d3}, intrahash = {0186031133dc122ffd6ff33ded32c911}, title = {Modularity clustering is force-directed layout}, url = {http://www.citebase.org/abstract?id=oai:arXiv.org:0807.4052}, year = 2008 } @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 }