With social media and the according social and ubiquitous applications
nding their way into everyday life, there is a rapidly growing amount of user
nerated content yielding explicit and implicit network structures. We
nsider social activities and phenomena as proxies for user relatedness. Such
tivities are represented in so-called social interaction networks or evidence
tworks, with different degrees of explicitness. We focus on evidence networks
ntaining relations on users, which are represented by connections between
dividual nodes. Explicit interaction networks are then created by specific
er actions, for example, when building a friend network. On the other hand,
re implicit networks capture user traces or evidences of user actions as
served in Web portals, blogs, resource sharing systems, and many other social
rvices. These implicit networks can be applied for a broad range of analysis
thods instead of using expensive gold-standard information.
In this paper, we analyze different properties of a set of networks in social
dia. We show that there are dependencies and correlations between the
tworks. These allow for drawing reciprocal conclusions concerning pairs of
tworks, based on the assessment of structural correlations and ranking
terchangeability. Additionally, we show how these inter-network correlations
n be used for assessing the results of structural analysis techniques, e.g.,
mmunity mining methods.

@misc{mitzlaff2013userrelatedness, author = {Mitzlaff, Folke and Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd}, title = {User-Relatedness and Community Structure in Social Interaction Networks}, year = {2013}, note = {cite arxiv:1309.3888}, url = {http://arxiv.org/abs/1309.3888}, keywords = {2013, community, evidence, iteg, itegpub, l3s, myown, networks, social}, abstract = {With social media and the according social and ubiquitous applicationsfinding their way into everyday life, there is a rapidly growing amount of usergenerated content yielding explicit and implicit network structures. Weconsider social activities and phenomena as proxies for user relatedness. Suchactivities are represented in so-called social interaction networks or evidencenetworks, with different degrees of explicitness. We focus on evidence networkscontaining relations on users, which are represented by connections betweenindividual nodes. Explicit interaction networks are then created by specificuser actions, for example, when building a friend network. On the other hand,more implicit networks capture user traces or evidences of user actions asobserved in Web portals, blogs, resource sharing systems, and many other socialservices. These implicit networks can be applied for a broad range of analysismethods instead of using expensive gold-standard information. In this paper, we analyze different properties of a set of networks in socialmedia. We show that there are dependencies and correlations between thenetworks. These allow for drawing reciprocal conclusions concerning pairs ofnetworks, based on the assessment of structural correlations and rankinginterchangeability. Additionally, we show how these inter-network correlationscan be used for assessing the results of structural analysis techniques, e.g.,community mining methods.} }

%0 = misc %A = Mitzlaff, Folke and Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd %B = } %C = %D = 2013 %I = %T = User-Relatedness and Community Structure in Social Interaction Networks} %U = http://arxiv.org/abs/1309.3888

@article{mitzlaff2013userrelatedness, author = {Mitzlaff, Folke and Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd}, title = {User-Relatedness and Community Structure in Social Interaction Networks}, journal = {CoRR/abs}, year = {2013}, volume = {1309.3888}, keywords = {2013, data, iteg, itegpub, l3s, mining, myown, social, ubiquitous, venus, web} }

%0 = article %A = Mitzlaff, Folke and Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd %D = 2013 %T = User-Relatedness and Community Structure in Social Interaction Networks

The combination of ubiquitous and social computing is an emerging
esearch area which integrates different but complementary methods,
echniques and tools. In this paper, we focus on the Ubicon platform,
ts applications, and a large spectrum of analysis results.

bicon provides an extensible framework for building and hosting applications
argeting both ubiquitous and social environments. We summarize the
rchitecture and exemplify its implementation using four real-world
pplications built on top of Ubicon. In addition, we discuss several
cientific experiments in the context of these applications in order
o give a better picture of the potential of the framework, and discuss
nalysis results using several real-world data sets collected utilizing
bicon.

@article{mueller-2014b, author = {Atzmueller, Martin and Becker, Martin and Kibanov, Mark and Scholz, Christoph and Doerfel, Stephan and Hotho, Andreas and Macek, Bjoern-Elmar and Mitzlaff, Folke and Mueller, Juergen and Stumme, Gerd}, title = {Ubicon and its Applications for Ubiquitous Social Computing}, journal = {New Review of Hypermedia and Multimedia}, year = {2014}, volume = {1}, number = {20}, pages = {53--77}, url = {http://dx.doi.org/10.1080/13614568.2013.873488}, doi = {10.1080/13614568.2013.873488}, issn = {1361-4568}, keywords = {2014, applications, computing, myown, social, ubicon, ubiquitous}, abstract = {The combination of ubiquitous and social computing is an emerging research area which integrates different but complementary methods, techniques and tools. In this paper, we focus on the Ubicon platform, its applications, and a large spectrum of analysis results. Ubicon provides an extensible framework for building and hosting applications targeting both ubiquitous and social environments. We summarize the architecture and exemplify its implementation using four real-world applications built on top of Ubicon. In addition, we discuss several scientific experiments in the context of these applications in order to give a better picture of the potential of the framework, and discuss analysis results using several real-world data sets collected utilizing Ubicon.} }

%0 = article %A = Atzmueller, Martin and Becker, Martin and Kibanov, Mark and Scholz, Christoph and Doerfel, Stephan and Hotho, Andreas and Macek, Bjoern-Elmar and Mitzlaff, Folke and Mueller, Juergen and Stumme, Gerd %D = 2014 %T = Ubicon and its Applications for Ubiquitous Social Computing %U = http://dx.doi.org/10.1080/13614568.2013.873488

@inproceedings{atzmueller2013towards, author = {Atzmueller, Martin and Hilgenberg, Katy}, title = {Towards Capturing Social Interactions with SDCF: An Extensible Framework for Mobile Sensing and Ubiquitous Data Collection}, booktitle = {Proc. 4th International Workshop on Modeling Social Media (MSM 2013), Hypertext 2013}, publisher = {ACM Press}, address = {New York, NY, USA}, year = {2013}, keywords = {2013, collection, data, interaction, iteg, itegpub, l3s, mobile, sensing, social, venus} }

%0 = inproceedings %A = Atzmueller, Martin and Hilgenberg, Katy %B = Proc. 4th International Workshop on Modeling Social Media (MSM 2013), Hypertext 2013 %C = New York, NY, USA %D = 2013 %I = ACM Press %T = Towards Capturing Social Interactions with SDCF: An Extensible Framework for Mobile Sensing and Ubiquitous Data Collection

Applications of the Social Web are ubiquitous and have become an integral part of everyday life: Users make friends, for example, with the help of online social networks, share thoughts via Twitter, or collaboratively write articles in Wikipedia. All such interactions leave digital traces; thus, users participate in the creation of heterogeneous, distributed, collaborative data collections. In linguistics, the

@article{mitzlaff2014social, author = {Mitzlaff, Folke and Atzmueller, Martin and Hotho, Andreas and Stumme, Gerd}, title = {The social distributional hypothesis: a pragmatic proxy for homophily in online social networks}, journal = {Social Network Analysis and Mining}, publisher = {Springer Vienna}, year = {2014}, volume = {4}, number = {1}, url = {http://dx.doi.org/10.1007/s13278-014-0216-2}, doi = {10.1007/s13278-014-0216-2}, issn = {1869-5450}, keywords = {2014, distributional, hypothesis, itegpub, myown, sitc, social}, abstract = {Applications of the Social Web are ubiquitous and have become an integral part of everyday life: Users make friends, for example, with the help of online social networks, share thoughts via Twitter, or collaboratively write articles in Wikipedia. All such interactions leave digital traces; thus, users participate in the creation of heterogeneous, distributed, collaborative data collections. In linguistics, the } }

%0 = article %A = Mitzlaff, Folke and Atzmueller, Martin and Hotho, Andreas and Stumme, Gerd %D = 2014 %I = Springer Vienna %T = The social distributional hypothesis: a pragmatic proxy for homophily in online social networks %U = http://dx.doi.org/10.1007/s13278-014-0216-2

@incollection{atzmueller2013social, author = {Atzmueller, Martin}, title = {Social Behavior in Mobile Social Networks: Characterizing Links, Roles and Communities}, editor = {Chin, Alvin and Zhang, Daqing}, booktitle = {Mobile Social Networking: An Innovative Approach}, publisher = {Springer Verlag}, address = {Heidelberg, Germany}, year = {2013}, keywords = {2013, analysis, iteg, itegpub, l3s, media, network, social, venus} }

%0 = incollection %A = Atzmueller, Martin %B = Mobile Social Networking: An Innovative Approach %C = Heidelberg, Germany %D = 2013 %I = Springer Verlag %T = Social Behavior in Mobile Social Networks: Characterizing Links, Roles and Communities

@incollection{mitzlaff2013semantics, author = {Mitzlaff, Folke and Atzmueller, Martin and Stumme, Gerd and Hotho, Andreas}, title = {Semantics of User Interaction in Social Media}, editor = {Ghoshal, Gourab and Poncela-Casasnovas, Julia and Tolksdorf, Robert}, booktitle = {Complex Networks IV}, series = {Studies in Computational Intelligence}, publisher = {Springer Verlag}, address = {Heidelberg, Germany}, year = {2013}, volume = {476}, doi = {10.1007/978-3-642-36844-8_2}, keywords = {2013, interaction, iteg, itegpub, l3s, media, myown, social, user, venus} }

%0 = incollection %A = Mitzlaff, Folke and Atzmueller, Martin and Stumme, Gerd and Hotho, Andreas %B = Complex Networks IV %C = Heidelberg, Germany %D = 2013 %I = Springer Verlag %T = Semantics of User Interaction in Social Media

@article{schulz2013rechtliche, author = {Schulz, Thomas and Skistims, Hendrik and Zirfas, Julia and Atzmueller, Martin and Scholz, Christoph}, title = {Rechtliche Ausgestaltung sozialer Konferenzplattformen}, journal = {ZD}, year = {2013}, volume = {2}, pages = {60--65}, keywords = {2013, analysis, conferator, iteg, itegpub, l3s, media, social, venus} }

%0 = article %A = Schulz, Thomas and Skistims, Hendrik and Zirfas, Julia and Atzmueller, Martin and Scholz, Christoph %D = 2013 %T = Rechtliche Ausgestaltung sozialer Konferenzplattformen

@book{rothberghofer2013proceedings,, title = {Proceedings of the 2013 International Smart University Workshop (SmartU 2013)}, editor = {Roth-Berghofer, Thomas and Oussena, Samia and Atzmueller, Martin}, publisher = {CONTEXT 2013}, address = {Annecy, France}, year = {2013}, keywords = {2013, iteg, itegpub, l3s, mining, smart, social, ubiquitous, university, workshop} }

%0 = book %C = Annecy, France %D = 2013 %I = CONTEXT 2013 %T = Proceedings of the 2013 International Smart University Workshop (SmartU 2013)

@proceedings{CAH:12,, title = {Proceedings MSM 2012: Workshop on Modeling Social Media -- Collective Intelligence in Social Media}, editor = {Chin, Alvin and Atzmueller, Martin and Helic, Denis}, publisher = {ACM Press}, address = {New York, NY, USA}, year = {2012}, keywords = {2012, collective, data, intelligence, itegpub, media, mining, modeling, msm, proceedings, social, ubiquitous, venus} }

%0 = proceedings %B = } %C = New York, NY, USA %D = 2012 %I = ACM Press %T = Proceedings MSM 2012: Workshop on Modeling Social Media -- Collective Intelligence in Social Media} %U =

@inproceedings{mitzlaff2011semantics, author = {Mitzlaff, Folke and Atzmueller, Martin and Stumme, Gerd and Hotho, Andreas}, title = {On the Semantics of User Interaction in Social Media (Extended Abstract, Resubmission)}, booktitle = {Proc. LWA 2013 (KDML Special Track)}, publisher = {University of Bamberg}, address = {Bamberg, Germany}, year = {2011}, keywords = {2013, data, iteg, itegpub, l3s, mining, myown, social, ubiquitous, venus, web} }

%0 = inproceedings %A = Mitzlaff, Folke and Atzmueller, Martin and Stumme, Gerd and Hotho, Andreas %B = Proc. LWA 2013 (KDML Special Track) %C = Bamberg, Germany %D = 2011 %I = University of Bamberg %T = On the Semantics of User Interaction in Social Media (Extended Abstract, Resubmission)

@inproceedings{kibanov2013evolution, author = {Kibanov, Mark and Atzmueller, Martin and Scholz, Christoph and Stumme, Gerd}, title = {On the Evolution of Contacts and Communities in Networks of Face-to-Face Proximity}, booktitle = {Proc. IEEE CPSCom 2013}, publisher = {IEEE Computer Society}, address = {Boston, MA, USA}, year = {2013}, keywords = {2013, community, conferator, face-to-face, iteg, itegpub, l3s, mining, myown, sna, social, venus} }

%0 = inproceedings %A = Kibanov, Mark and Atzmueller, Martin and Scholz, Christoph and Stumme, Gerd %B = Proc. IEEE CPSCom 2013 %C = Boston, MA, USA %D = 2013 %I = IEEE Computer Society %T = On the Evolution of Contacts and Communities in Networks of Face-to-Face Proximity

@article{Atzmueller:12, author = {Atzmueller, Martin}, title = {Mining Social Media}, journal = {Informatik Spektrum}, year = {2012}, volume = {35}, number = {2}, pages = {132-135}, keywords = {2012, analysis, community, data, itegpub, media, sentiment, social, socialnetworks} }

%0 = article %A = Atzmueller, Martin %D = 2012 %T = Mining Social Media

@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}, keywords = {2013, analysis, iteg, itegpub, l3s, link, myown, network, prediction, social} }

%0 = inproceedings %A = Scholz, Christoph and Atzmueller, Martin and Kibanov, Mark and Stumme, Gerd %B = ASONAM %D = 2013 %T = How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks

@article{atzmueller2013exploratory, author = {Atzmueller, Martin and Lemmerich, Florian}, title = {Exploratory Pattern Mining on Social Media using Geo-References and Social Tagging Information}, journal = {International Journal of Web Science (Special Issue on Social Web Search and Mining)}, year = {2013}, volume = {2}, number = {1/2}, keywords = {2013, analysis, exploratory, iteg, itegpub, l3s, media, mining, pattern, social, venus} }

%0 = article %A = Atzmueller, Martin and Lemmerich, Florian %D = 2013 %T = Exploratory Pattern Mining on Social Media using Geo-References and Social Tagging Information

@inproceedings{kibanov2013evolution, author = {Kibanov, Mark and Atzmueller, Martin and Scholz, Christoph and Stumme, Gerd}, title = {Evolution of Contacts and Communities in Networks of Face-to-Face Proximity (Extended Abstract, Resubmission)}, booktitle = {Proc. LWA 2013 (KDML Special Track)}, publisher = {University of Bamberg}, address = {Bamberg, Germany}, year = {2013}, keywords = {2013, conferator, data, iteg, itegpub, l3s, mining, myown, social, ubiquitous, venus} }

%0 = inproceedings %A = Kibanov, Mark and Atzmueller, Martin and Scholz, Christoph and Stumme, Gerd %B = Proc. LWA 2013 (KDML Special Track) %C = Bamberg, Germany %D = 2013 %I = University of Bamberg %T = Evolution of Contacts and Communities in Networks of Face-to-Face Proximity (Extended Abstract, Resubmission)

@incollection{LA:12, author = {Lemmerich, Florian and Atzmueller, Martin}, title = {Describing Locations using Tags and Images: Explorative Pattern Mining in Social Media}, booktitle = {Modeling and Mining Ubiquitous Social Media}, series = {LNAI}, publisher = {Springer Verlag}, address = {Heidelberg, Germany}, year = {2012}, volume = {7472}, url = {http://www.kde.cs.uni-kassel.de/atzmueller/paper/lemmerich-explorative-pattern-mining-socia-media-lnai-2012.pdf}, keywords = {2012, collective, data, describing, explorative, images, intelligence, itegpub, locations, media, mining, social, tags, ubiquitous, venus} }

%0 = incollection %A = Lemmerich, Florian and Atzmueller, Martin %B = Modeling and Mining Ubiquitous Social Media %C = Heidelberg, Germany %D = 2012 %I = Springer Verlag %T = Describing Locations using Tags and Images: Explorative Pattern Mining in Social Media %U = http://www.kde.cs.uni-kassel.de/atzmueller/paper/lemmerich-explorative-pattern-mining-socia-media-lnai-2012.pdf

The information contained in social tagging systems is often modelled as a graph of connections between users, items and tags. Recommendation algorithms such as FolkRank, have the potential to leverage complex relationships in the data, corresponding to multiple hops in the graph. We present an in-depth analysis and evaluation of graph models for social tagging data and propose novel adaptations and extensions of FolkRank to improve tag recommendations. We highlight implicit assumptions made by the widely used folksonomy model, and propose an alternative and more accurate graph-representation of the data. Our extensions of FolkRank address the new item problem by incorporating content data into the algorithm, and significantly improve prediction results on unpruned datasets. Our adaptations address issues in the iterative weight spreading calculation that potentially hinder FolkRank's ability to leverage the deep graph as an information source. Moreover, we evaluate the benefit of considering each deeper level of the graph, and present important insights regarding the characteristics of social tagging data in general. Our results suggest that the base assumption made by conventional weight propagation methods, that closeness in the graph always implies a positive relationship, does not hold for the social tagging domain.

@article{landia2013deeper, author = {Landia, Nikolas and Doerfel, Stephan and Jäschke, Robert and Anand, Sarabjot Singh and Hotho, Andreas and Griffiths, Nathan}, title = {Deeper Into the Folksonomy Graph: FolkRank Adaptations and Extensions for Improved Tag Recommendations}, journal = {cs.IR}, year = {2013}, volume = {1310.1498}, url = {http://arxiv.org/abs/1310.1498}, keywords = {2013, bookmarking, collaborative, folkrank, folksonomy, graph, iteg, itegpub, l3s, recommender, social, tagging}, abstract = {The information contained in social tagging systems is often modelled as a graph of connections between users, items and tags. Recommendation algorithms such as FolkRank, have the potential to leverage complex relationships in the data, corresponding to multiple hops in the graph. We present an in-depth analysis and evaluation of graph models for social tagging data and propose novel adaptations and extensions of FolkRank to improve tag recommendations. We highlight implicit assumptions made by the widely used folksonomy model, and propose an alternative and more accurate graph-representation of the data. Our extensions of FolkRank address the new item problem by incorporating content data into the algorithm, and significantly improve prediction results on unpruned datasets. Our adaptations address issues in the iterative weight spreading calculation that potentially hinder FolkRank's ability to leverage the deep graph as an information source. Moreover, we evaluate the benefit of considering each deeper level of the graph, and present important insights regarding the characteristics of social tagging data in general. Our results suggest that the base assumption made by conventional weight propagation methods, that closeness in the graph always implies a positive relationship, does not hold for the social tagging domain.} }

%0 = article %A = Landia, Nikolas and Doerfel, Stephan and Jäschke, Robert and Anand, Sarabjot Singh and Hotho, Andreas and Griffiths, Nathan %D = 2013 %T = Deeper Into the Folksonomy Graph: FolkRank Adaptations and Extensions for Improved Tag Recommendations %U = http://arxiv.org/abs/1310.1498

@misc{atzmueller2013conferator, author = {Atzmueller, Martin and Kibanov, Mark and Scholz, Christoph and Stumme, Gerd}, title = {Conferator - a Social System for Conference and Contact Management}, publisher = {INFORMATIK 2013}, year = {2013}, keywords = {2013, conferator, data, iteg, itegpub, l3s, mining, myown, social, ubiquitous, venus} }

%0 = misc %A = Atzmueller, Martin and Kibanov, Mark and Scholz, Christoph and Stumme, Gerd %B = } %C = %D = 2013 %I = INFORMATIK 2013 %T = Conferator - a Social System for Conference and Contact Management} %U =

Since the rise of collaborative tagging systems on the web, the tag recommendation task - suggesting suitable tags to users of such systems while they add resources to their collection - has been tackled. However, the (offline) evaluation of tag recommendation algorithms usually suffers from difficulties like the sparseness of the data or the cold start problem for new resources or users. Previous studies therefore often used so-called post-cores (specific subsets of the original datasets) for their experiments. In this paper, we conduct a large-scale experiment in which we analyze different tag recommendation algorithms on different cores of three real-world datasets. We show, that a recommender's performance depends on the particular core and explore correlations between performances on different cores.

@inproceedings{doerfel2013analysis, author = {Doerfel, Stephan and Jäschke, Robert}, title = {An analysis of tag-recommender evaluation procedures}, booktitle = {Proceedings of the 7th ACM conference on Recommender systems}, series = {RecSys '13}, publisher = {ACM}, address = {New York, NY, USA}, year = {2013}, pages = {343--346}, url = {https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2013analysis.pdf}, doi = {10.1145/2507157.2507222}, isbn = {978-1-4503-2409-0}, keywords = {2013, bibsonomy, bookmarking, collaborative, core, evaluation, folkrank, folksonomy, graph, iteg, itegpub, l3s, recommender, social, tagging}, abstract = {Since the rise of collaborative tagging systems on the web, the tag recommendation task -- suggesting suitable tags to users of such systems while they add resources to their collection -- has been tackled. However, the (offline) evaluation of tag recommendation algorithms usually suffers from difficulties like the sparseness of the data or the cold start problem for new resources or users. Previous studies therefore often used so-called post-cores (specific subsets of the original datasets) for their experiments. In this paper, we conduct a large-scale experiment in which we analyze different tag recommendation algorithms on different cores of three real-world datasets. We show, that a recommender's performance depends on the particular core and explore correlations between performances on different cores.} }

%0 = inproceedings %A = Doerfel, Stephan and Jäschke, Robert %B = Proceedings of the 7th ACM conference on Recommender systems %C = New York, NY, USA %D = 2013 %I = ACM %T = An analysis of tag-recommender evaluation procedures %U = https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2013analysis.pdf