| Author | Title | Year | Journal/Proceedings | Reftype | DOI/URL |
|---|---|---|---|---|---|
| Atzmueller, M. | Social Behavior in Mobile Social Networks: Characterizing Links, Roles and Communities [BibTeX] |
2013 | Mobile Social Networking: An Innovative Approach | incollection | |
BibTeX:
@incollection{atzmueller2013social,
author = {Atzmueller, Martin},
title = {{Social Behavior in Mobile Social Networks: Characterizing Links, Roles and Communities}},
booktitle = {Mobile Social Networking: An Innovative Approach},
publisher = {Springer Verlag},
year = {2013}
}
|
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| Scholz, C., Atzmueller, M., Kibanov, M. & Stumme, G. | How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks [BibTeX] |
2013 | ASONAM | inproceedings | |
BibTeX:
@inproceedings{scholz2013people,
author = {Scholz, Christoph and Atzmueller, Martin and Kibanov, Mark and Stumme, Gerd},
title = {How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks},
booktitle = {ASONAM},
year = {2013}
}
|
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| Scholz, C., Atzmueller, M., Kibanov, M. & Stumme, G. | How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks | 2013 | Advances in Social Networks Analysis and Mining (ASONAM), 2013 International Conference on | inproceedings | |
| 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. 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. |
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BibTeX:
@inproceedings{scholz2013people,
author = {Scholz, Christoph and Atzmueller, Martin and Kibanov, Mark and Stumme, Gerd},
title = {How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks},
booktitle = {Advances in Social Networks Analysis and Mining (ASONAM), 2013 International Conference on},
year = {2013}
}
|
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| Atzmueller, M. | Mining Social Media: Key Players, Sentiments, and Communities [BibTeX] |
2012 | WIREs: Data Mining and Knowledge Discovery | article | |
BibTeX:
@article{Atzmueller:12c,
author = {Atzmueller, Martin},
title = {{Mining Social Media: Key Players, Sentiments, and Communities}},
journal = {WIREs: Data Mining and Knowledge Discovery},
year = {2012},
volume = {In Press}
}
|
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| BATAGELJ, V. | Social Network Analysis, Large-scale [BibTeX] |
2009 | Encyclopedia of Complexity and System Science | article | URL |
BibTeX:
@article{batagelj2009social,
author = {BATAGELJ, VLADIMIR},
title = {Social Network Analysis, Large-scale},
journal = {Encyclopedia of Complexity and System Science},
year = {2009},
url = {http://vlado.fmf.uni-lj.si/pub/networks/doc/mix/LargeSNA.pdf}
}
|
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| Brandes, U., Kenis, P., Lerner, J. & van Raaij, D. | Network analysis of collaboration structure in Wikipedia | 2009 | WWW '09: Proceedings of the 18th international conference on World wide web | inproceedings | DOIURL |
| 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. | |||||
BibTeX:
@inproceedings{1526808,
author = {Brandes, Ulrik and Kenis, Patrick and Lerner, J\"{u}rgen and van Raaij, Denise},
title = {Network analysis of collaboration structure in Wikipedia},
booktitle = {WWW '09: Proceedings of the 18th international conference on World wide web},
publisher = {ACM},
year = {2009},
pages = {731--740},
url = {http://portal.acm.org/citation.cfm?id=1526808},
doi = {http://doi.acm.org/10.1145/1526709.1526808}
}
|
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| Das, G., Koudas, N., Papagelis, M. & Puttaswamy, S. | Efficient sampling of information in social networks | 2008 | SSM '08: Proceeding of the 2008 ACM workshop on Search in social media | inproceedings | DOIURL |
| 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. | |||||
BibTeX:
@inproceedings{das2008efficient,
author = {Das, Gautam and Koudas, Nick and Papagelis, Manos and Puttaswamy, Sushruth},
title = {Efficient sampling of information in social networks},
booktitle = {SSM '08: Proceeding of the 2008 ACM workshop on Search in social media},
publisher = {ACM},
year = {2008},
pages = {67--74},
url = {http://portal.acm.org/citation.cfm?id=1458583.1458594},
doi = {http://doi.acm.org/10.1145/1458583.1458594}
}
|
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| Krause, B., Jäschke, R., Hotho, A. & Stumme, G. | Logsonomy - Social Information Retrieval with Logdata | 2008 | HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia | inproceedings | DOIURL |
| Abstract: Social bookmarking systems constitute an established rt of the Web 2.0. In such systems ers describe bookmarks by keywords lled tags. The structure behind these social stems, called folksonomies, can be viewed a tripartite hypergraph of user, tag and resource des. This underlying network shows ecific structural properties that explain its owth and the possibility of serendipitous ploration. day’s search engines represent the gateway retrieve information from the World Wide b. Short queries typically consisting of o to three words describe a user’s information ed. In response to the displayed sults of the search engine, users click on e links of the result page as they expect e answer to be of relevance. is clickdata can be represented as a folksonomy which queries are descriptions of icked URLs. The resulting network structure, ich we will term logsonomy is very milar to the one of folksonomies. In order find out about its properties, we analyze e topological characteristics of the tripartite pergraph of queries, users and bookmarks a large snapshot of del.icio.us and query logs of two large search engines. l of the three datasets show small world operties. The tagging behavior of users, ich is explained by preferential attachment the tags in social bookmark systems, is flected in the distribution of single query rds in search engines. We can conclude at the clicking behaviour of search engine ers based on the displayed search results d the tagging behaviour of social bookmarking ers is driven by similar dynamics. |
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BibTeX:
@inproceedings{krause2008logsonomy,
author = {Krause, Beate and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd},
title = {Logsonomy - Social Information Retrieval with Logdata},
booktitle = {HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia},
publisher = {ACM},
year = {2008},
pages = {157--166},
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},
doi = {http://doi.acm.org/10.1145/1379092.1379123}
}
|
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| Leskovec, J. & Horvitz, E. | Planetary-scale views on a large instant-messaging network | 2008 | WWW '08: Proceeding of the 17th international conference on World Wide Web | inproceedings | DOIURL |
| 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. | |||||
BibTeX:
@inproceedings{1367620,
author = {Leskovec, Jure and Horvitz, Eric},
title = {Planetary-scale views on a large instant-messaging network},
booktitle = {WWW '08: Proceeding of the 17th international conference on World Wide Web},
publisher = {ACM},
year = {2008},
pages = {915--924},
url = {http://portal.acm.org/citation.cfm?id=1367620},
doi = {http://doi.acm.org/10.1145/1367497.1367620}
}
|
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| Brandes, U. & Lerner, J. | Role-equivalent Actors in Networks | 2007 | ICFCA 2007 Satellite Workshop on Social Network Analysis and Conceptual Structures: Exploring Opportunities | inproceedings | URL |
| 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 ructure which does not coincide with the structure of dense groups. is papers gives a survey over formalizations of network-positions with a special emphasis on the use of algebraic notions. |
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BibTeX:
@inproceedings{Brandes07Role,
author = {Brandes, Ulrik and Lerner, Jürgen},
title = {Role-equivalent Actors in Networks},
booktitle = {ICFCA 2007 Satellite Workshop on Social Network Analysis and Conceptual Structures: Exploring Opportunities},
year = {2007},
url = {http://www.inf.uni-konstanz.de/algo/publications/bl-rean-07.pdf}
}
|
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| Carrington, P. J. | Models and methods in social network analysis | 2007 | book | URL | |
| Abstract: Literaturangaben | |||||
BibTeX:
@book{Carrington:2007,
author = {Carrington, Peter J.},
title = {Models and methods in social network analysis},
publisher = {Cambridge Univ. Press Cambridge [u.a.]},
year = {2007},
url = {http://opac.bibliothek.uni-kassel.de/DB=23/PPN?PPN=190999837}
}
|
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| Proceedings of the 2nd Workshop on Semantic Network Analysis [BibTeX] |
2006 | proceedings | URL | ||
BibTeX:
@proceedings{alani2006proceedings,,
title = {Proceedings of the 2nd Workshop on Semantic Network Analysis},
year = {2006},
url = {http://www.kde.cs.uni-kassel.de/ws/sna2006/}
}
|
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| Schmitz, C., Hotho, A., Jäschke, R. & Stumme, G. | Mining Association Rules in Folksonomies | 2006 | Data Science and Classification. Proceedings of the 10th IFCS Conf. | inproceedings | URL |
| Abstract: Social bookmark tools are rapidly emerging on the Web. In such
stems users are setting up lightweight conceptual structures lled folksonomies. These systems provide currently relatively few ructure. We discuss in this paper, how association rule mining n be adopted to analyze and structure folksonomies, and how the results can be used r ontology learning and supporting emergent semantics. We monstrate our approach on a large scale dataset stemming from an line system. |
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BibTeX:
@inproceedings{schmitz2006mining,
author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
title = {Mining Association Rules in Folksonomies},
booktitle = {Data Science and Classification. Proceedings of the 10th IFCS Conf.},
publisher = {Springer},
year = {2006},
pages = {261--270},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006mining.pdf}
}
|
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| Scott, J. | Social network analysis | 2005 | book | URL | |
| Abstract: Literaturverz. S. [193] - 204 | |||||
BibTeX:
@book{Scott:2005,
author = {Scott, John},
title = {Social network analysis},
publisher = {Sage Publ. London [u.a.]},
year = {2005},
url = {http://opac.bibliothek.uni-kassel.de/DB=23/PPN?PPN=128222697}
}
|
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| Proceedings of the First Workshop on Semantic Network Analysis [BibTeX] |
2005 | proceedings | URL | ||
BibTeX:
@proceedings{stumme05semanticnetworkanalysis,,
title = {Proceedings of the First Workshop on Semantic Network Analysis },
publisher = {CEUR Proceedings},
year = {2005},
url = {http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-171/}
}
|
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| Freeman, L. C. | Finding Social Groups: A Meta-Analysis of the Southern Women Data [BibTeX] |
2003 | Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers | inproceedings | |
BibTeX:
@inproceedings{freeman03finding,
author = {Freeman, Linton C.},
title = {Finding Social Groups: A Meta-Analysis of the Southern Women Data},
booktitle = {Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers},
publisher = {National Academies Press},
year = {2003}
}
|
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