Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.

@inproceedings{zoller2015publication, author = {Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas}, title = {On Publication Usage in a Social Bookmarking System}, booktitle = {Proceedings of the 2015 ACM Conference on Web Science}, year = {2015}, keywords = {2015, altmetrics, bookmarking, impact, myown, publication, social, usage}, abstract = {Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.} }

%0 = inproceedings %A = Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas %B = Proceedings of the 2015 ACM Conference on Web Science %D = 2015 %T = On Publication Usage in a Social Bookmarking System

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{atzmueller2014ubicon, 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 = {20}, number = {1}, pages = {53--77}, url = {http://www.tandfonline.com/doi/abs/10.1080/13614568.2013.873488}, doi = {10.1080/13614568.2013.873488}, keywords = {2014, analytics, mining, 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://www.tandfonline.com/doi/abs/10.1080/13614568.2013.873488

@inproceedings{doerfel2014social, author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus}, title = {How Social is Social Tagging?}, booktitle = {Proceedings of the 23rd International World Wide Web Conference}, series = {WWW 2014}, publisher = {ACM}, address = {New York, NY, USA}, year = {2014}, keywords = {2014, WWW, analyis, behavior, log, myown, social, tagging} }

%0 = inproceedings %A = Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus %B = Proceedings of the 23rd International World Wide Web Conference %C = New York, NY, USA %D = 2014 %I = ACM %T = How Social is Social Tagging?

Social tagging systems have established themselves as an important part in
day's web and have attracted the interest from our research community in a
riety of investigations. The overall vision of our community is that simply
rough interactions with the system, i.e., through tagging and sharing of
sources, users would contribute to building useful semantic structures as
ll as resource indexes using uncontrolled vocabulary not only due to the
sy-to-use mechanics. Henceforth, a variety of assumptions about social
gging systems have emerged, yet testing them has been difficult due to the
sence of suitable data. In this work we thoroughly investigate three
ailable assumptions - e.g., is a tagging system really social? - by examining
ve log data gathered from the real-world public social tagging system
bSonomy. Our empirical results indicate that while some of these assumptions
ld to a certain extent, other assumptions need to be reflected and viewed in
very critical light. Our observations have implications for the design of
ture search and other algorithms to better reflect the actual user behavior.

@misc{doerfel2014course, author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus}, title = {Of course we share! Testing Assumptions about Social Tagging Systems}, year = {2014}, note = {cite arxiv:1401.0629}, url = {http://arxiv.org/abs/1401.0629}, keywords = {2014, myown, share, social, tagging}, abstract = {Social tagging systems have established themselves as an important part intoday's web and have attracted the interest from our research community in avariety of investigations. The overall vision of our community is that simplythrough interactions with the system, i.e., through tagging and sharing ofresources, users would contribute to building useful semantic structures aswell as resource indexes using uncontrolled vocabulary not only due to theeasy-to-use mechanics. Henceforth, a variety of assumptions about socialtagging systems have emerged, yet testing them has been difficult due to theabsence of suitable data. In this work we thoroughly investigate threeavailable assumptions - e.g., is a tagging system really social? - by examininglive log data gathered from the real-world public social tagging systemBibSonomy. Our empirical results indicate that while some of these assumptionshold to a certain extent, other assumptions need to be reflected and viewed ina very critical light. Our observations have implications for the design offuture search and other algorithms to better reflect the actual user behavior.} }

%0 = misc %A = Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus %B = } %C = %D = 2014 %I = %T = Of course we share! Testing Assumptions about Social Tagging Systems} %U = http://arxiv.org/abs/1401.0629

@proceedings{jannach2014proceedings,, title = {Proceedings of the 6th Workshop on Recommender Systems and the Social
Web (RSWeb 2014) co-located with the 8th ACM Conference on Recommender
Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014}, editor = {Jannach, Dietmar and Freyne, Jill and Geyer, Werner and Guy, Ido and Hotho, Andreas and Mobasher, Bamshad}, series = {CEUR Workshop Proceedings}, publisher = {CEUR-WS.org}, year = {2014}, volume = {1271}, url = {http://ceur-ws.org/Vol-1271}, keywords = {2014, myown, proceedings, recommender, social, workshop} }

%0 = proceedings %B = } %C = %D = 2014 %I = CEUR-WS.org %T = Proceedings of the 6th Workshop on Recommender Systems and the Social
Web (RSWeb 2014) co-located with the 8th ACM Conference on Recommender
Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014} %U = http://ceur-ws.org/Vol-1271

@inproceedings{jannach2014sixth, author = {Jannach, Dietmar and Freyne, Jill and Geyer, Werner and Guy, Ido and Hotho, Andreas and Mobasher, Bamshad}, title = {The sixth ACM RecSys workshop on recommender systems and the social
web}, booktitle = {Eighth ACM Conference on Recommender Systems, RecSys '14, Foster City, Silicon Valley, CA, USA - October 06 - 10, 2014}, year = {2014}, pages = {395}, url = {http://doi.acm.org/10.1145/2645710.2645786}, doi = {10.1145/2645710.2645786}, keywords = {2014, introduction, myown, recommender, social, workshop} }

%0 = inproceedings %A = Jannach, Dietmar and Freyne, Jill and Geyer, Werner and Guy, Ido and Hotho, Andreas and Mobasher, Bamshad %B = Eighth ACM Conference on Recommender Systems, RecSys '14, Foster City, Silicon Valley, CA, USA - October 06 - 10, 2014 %D = 2014 %T = The sixth ACM RecSys workshop on recommender systems and the social
web %U = http://doi.acm.org/10.1145/2645710.2645786

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{noKey, 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, myown, pragmatic, proxy, 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

When users interact with the Web today, they leave sequential digital trails
a massive scale. Examples of such human trails include Web navigation,
quences of online restaurant reviews, or online music play lists.
derstanding the factors that drive the production of these trails can be
eful for e.g., improving underlying network structures, predicting user
icks or enhancing recommendations. In this work, we present a general
proach called HypTrails for comparing a set of hypotheses about human trails
the Web, where hypotheses represent beliefs about transitions between
ates. Our approach utilizes Markov chain models with Bayesian inference. The
in idea is to incorporate hypotheses as informative Dirichlet priors and to
verage the sensitivity of Bayes factors on the prior for comparing hypotheses
th each other. For eliciting Dirichlet priors from hypotheses, we present an
aption of the so-called (trial) roulette method. We demonstrate the general
chanics and applicability of HypTrails by performing experiments with (i)
nthetic trails for which we control the mechanisms that have produced them
d (ii) empirical trails stemming from different domains including website
vigation, business reviews and online music played. Our work expands the
pertoire of methods available for studying human trails on the Web.

@misc{singer2014hyptrails, author = {Singer, Philipp and Helic, Denis and Hotho, Andreas and Strohmaier, Markus}, title = {HypTrails: A Bayesian Approach for Comparing Hypotheses about Human
Trails on the Web}, year = {2014}, note = {cite arxiv:1411.2844}, url = {http://arxiv.org/abs/1411.2844}, keywords = {2014, bayesian, comparing, hypotheses, myown, semantic, social}, abstract = {When users interact with the Web today, they leave sequential digital trailson a massive scale. Examples of such human trails include Web navigation,sequences of online restaurant reviews, or online music play lists.Understanding the factors that drive the production of these trails can beuseful for e.g., improving underlying network structures, predicting userclicks or enhancing recommendations. In this work, we present a generalapproach called HypTrails for comparing a set of hypotheses about human trailson the Web, where hypotheses represent beliefs about transitions betweenstates. Our approach utilizes Markov chain models with Bayesian inference. Themain idea is to incorporate hypotheses as informative Dirichlet priors and toleverage the sensitivity of Bayes factors on the prior for comparing hypotheseswith each other. For eliciting Dirichlet priors from hypotheses, we present anadaption of the so-called (trial) roulette method. We demonstrate the generalmechanics and applicability of HypTrails by performing experiments with (i)synthetic trails for which we control the mechanisms that have produced themand (ii) empirical trails stemming from different domains including websitenavigation, business reviews and online music played. Our work expands therepertoire of methods available for studying human trails on the Web.} }

%0 = misc %A = Singer, Philipp and Helic, Denis and Hotho, Andreas and Strohmaier, Markus %B = } %C = %D = 2014 %I = %T = HypTrails: A Bayesian Approach for Comparing Hypotheses about Human
Trails on the Web} %U = http://arxiv.org/abs/1411.2844

@article{strohmaier2014computational, author = {Strohmaier, Markus and Wagner, Claudia}, title = {Computational Social Science for the World Wide Web}, journal = {Intelligent Systems}, publisher = {IEEE }, year = {2014}, pages = {84-88}, keywords = {computational, social} }

%0 = article %A = Strohmaier, Markus and Wagner, Claudia %D = 2014 %I = IEEE %T = Computational Social Science for the World Wide Web

@book{atzmueller2013ubiquitous,, title = {Ubiquitous Social Media Analysis Third International Workshops, MUSE 2012, Bristol, UK, September 24, 2012, and MSM 2012, Milwaukee, WI, USA, June 25, 2012, Revised Selected Papers}, editor = {Atzmueller, Martin and Chin, Alvin and Helic, Denis and Hotho, Andreas}, publisher = {Imprint: Springer}, address = {Berlin, Heidelberg}, year = {2013}, url = {http://link.springer.com/book/10.1007/978-3-642-45392-2}, isbn = {9783642453915 3642453910 9783642453922 3642453929}, keywords = {2013, analysis, bibsonomy, media, myown, postproceedings, social, workshop} }

%0 = book %C = Berlin, Heidelberg %D = 2013 %I = Imprint: Springer %T = Ubiquitous Social Media Analysis Third International Workshops, MUSE 2012, Bristol, UK, September 24, 2012, and MSM 2012, Milwaukee, WI, USA, June 25, 2012, Revised Selected Papers %U = http://link.springer.com/book/10.1007/978-3-642-45392-2

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, myown, 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

@incollection{MASH:13, 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, media, myown, semantic, social, user} }

%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{journals/corr/MitzlaffABHS13, 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}, year = {2013}, volume = {abs/1309.3888}, url = {http://dblp.uni-trier.de/db/journals/corr/corr1309.html#MitzlaffABHS13}, keywords = {bibsonomy, relatedness, social, structure, user} }

%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. %U = http://dblp.uni-trier.de/db/journals/corr/corr1309.html#MitzlaffABHS13

@proceedings{conf/recsys/2013rsweb,, title = {Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), Hong Kong, China, October 13, 2013.}, editor = {Mobasher, Bamshad and Jannach, Dietmar and Geyer, Werner and Freyne, Jill and Hotho, Andreas and Anand, Sarabjot Singh and Guy, Ido}, booktitle = {RSWeb@RecSys}, series = {CEUR Workshop Proceedings}, publisher = {CEUR-WS.org}, year = {2013}, volume = {1066}, url = {http://ceur-ws.org/Vol-1066}, keywords = {2013, bibsonomy, l3s, myown, recommender, social, web, workshop} }

%0 = proceedings %B = RSWeb@RecSys} %C = %D = 2013 %I = CEUR-WS.org %T = Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), Hong Kong, China, October 13, 2013.} %U = http://ceur-ws.org/Vol-1066

@article{sun2013social, author = {Sun, Xiaoling and Kaur, Jasleen and Milojevic, Stasa and Flammini, Alessandro and Menczer, Filippo}, title = {Social Dynamics of Science}, journal = {Sci. Rep.}, publisher = {Macmillan Publishers Limited. All rights reserved}, year = {2013}, volume = {3}, url = {http://dx.doi.org/10.1038/srep01069}, keywords = {bibsonomy, dynamics, science, social, toread, web} }

%0 = article %A = Sun, Xiaoling and Kaur, Jasleen and Milojevic, Stasa and Flammini, Alessandro and Menczer, Filippo %D = 2013 %I = Macmillan Publishers Limited. All rights reserved %T = Social Dynamics of Science %U = http://dx.doi.org/10.1038/srep01069

@book{ACHH:12,, title = {Modeling and Mining Ubiquitous Social Media}, editor = {Atzmueller, Martin and Chin, Alvin and Helic, Denis and Hotho, Andreas}, series = {Lecture Notes in Computer Science}, publisher = {Springer Verlag}, address = {Heidelberg, Germany}, year = {2012}, volume = {7472}, url = {http://www.springer.com/computer/ai/book/978-3-642-33683-6}, keywords = {2012, everyaware, media, mining, modeling, myown, social, ubiquitous} }

%0 = book %C = Heidelberg, Germany %D = 2012 %I = Springer Verlag %T = Modeling and Mining Ubiquitous Social Media %U = http://www.springer.com/computer/ai/book/978-3-642-33683-6

The connection of ubiquitous and social computing is an emerging research area which is combining two prominent areas of computer science. In this paper, we tackle this topic from different angles: We describe data mining methods for ubiquitous and social data, specifically focusing on physical and social activities, and provide exemplary analysis results. Furthermore, we give an overview on the Ubicon platform which provides a framework for the creation and hosting of ubiquitous and social applications for diverse tasks and projects. Ubicon features the collection and analysis of both physical and social activities of users for enabling inter-connected applications in ubiquitous and social contexts. We summarize three real-world systems built on top of Ubicon, and exemplarily discuss the according mining and analysis aspects.

@inproceedings{mueller-2012, author = {Atzmueller, Martin and Becker, Martin and Doerfel, Stephan and Kibanov, Mark and Hotho, Andreas and Macek, Björn-Elmar and Mitzlaff, Folke and Mueller, Juergen and Scholz, Christoph and Stumme, Gerd}, title = {Ubicon: Observing Social and Physical Activities}, booktitle = {IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2012, Besançon, France, 20-23 November, 2012}, publisher = {IEEE}, address = {Washington, DC, USA}, year = {2012}, keywords = {2012, activities, everyaware, myown, observing, physical, social, ubicon}, abstract = {The connection of ubiquitous and social computing is an emerging research area which is combining two prominent areas of computer science. In this paper, we tackle this topic from different angles: We describe data mining methods for ubiquitous and social data, specifically focusing on physical and social activities, and provide exemplary analysis results. Furthermore, we give an overview on the Ubicon platform which provides a framework for the creation and hosting of ubiquitous and social applications for diverse tasks and projects. Ubicon features the collection and analysis of both physical and social activities of users for enabling inter-connected applications in ubiquitous and social contexts. We summarize three real-world systems built on top of Ubicon, and exemplarily discuss the according mining and analysis aspects.} }

%0 = inproceedings %A = Atzmueller, Martin and Becker, Martin and Doerfel, Stephan and Kibanov, Mark and Hotho, Andreas and Macek, Björn-Elmar and Mitzlaff, Folke and Mueller, Juergen and Scholz, Christoph and Stumme, Gerd %B = IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2012, Besançon, France, 20-23 November, 2012 %C = Washington, DC, USA %D = 2012 %I = IEEE %T = Ubicon: Observing Social and Physical Activities

@inproceedings{MASH:13b, 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, mining, myown, social, ubiquitous} }

%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)

We study the structure of the social graph of active Facebook users, the
rgest social network ever analyzed. We compute numerous features of the graph
cluding the number of users and friendships, the degree distribution, path
ngths, clustering, and mixing patterns. Our results center around three main
servations. First, we characterize the global structure of the graph,
termining that the social network is nearly fully connected, with 99.91% of
dividuals belonging to a single large connected component, and we confirm the
ix degrees of separation" phenomenon on a global scale. Second, by studying
e average local clustering coefficient and degeneracy of graph neighborhoods,
show that while the Facebook graph as a whole is clearly sparse, the graph
ighborhoods of users contain surprisingly dense structure. Third, we
aracterize the assortativity patterns present in the graph by studying the
sic demographic and network properties of users. We observe clear degree
sortativity and characterize the extent to which "your friends have more
iends than you". Furthermore, we observe a strong effect of age on friendship
eferences as well as a globally modular community structure driven by
tionality, but we do not find any strong gender homophily. We compare our
sults with those from smaller social networks and find mostly, but not
tirely, agreement on common structural network characteristics.

@misc{ugander2011anatomy, author = {Ugander, Johan and Karrer, Brian and Backstrom, Lars and Marlow, Cameron}, title = {The Anatomy of the Facebook Social Graph}, year = {2011}, note = {cite arxiv:1111.4503Comment: 17 pages, 9 figures, 1 table}, url = {http://arxiv.org/abs/1111.4503}, keywords = {facebook, graph, network, social}, abstract = {We study the structure of the social graph of active Facebook users, thelargest social network ever analyzed. We compute numerous features of the graphincluding the number of users and friendships, the degree distribution, pathlengths, clustering, and mixing patterns. Our results center around three mainobservations. First, we characterize the global structure of the graph,determining that the social network is nearly fully connected, with 99.91% ofindividuals belonging to a single large connected component, and we confirm the"six degrees of separation" phenomenon on a global scale. Second, by studyingthe average local clustering coefficient and degeneracy of graph neighborhoods,we show that while the Facebook graph as a whole is clearly sparse, the graphneighborhoods of users contain surprisingly dense structure. Third, wecharacterize the assortativity patterns present in the graph by studying thebasic demographic and network properties of users. We observe clear degreeassortativity and characterize the extent to which "your friends have morefriends than you". Furthermore, we observe a strong effect of age on friendshippreferences as well as a globally modular community structure driven bynationality, but we do not find any strong gender homophily. We compare ourresults with those from smaller social networks and find mostly, but notentirely, agreement on common structural network characteristics.} }

%0 = misc %A = Ugander, Johan and Karrer, Brian and Backstrom, Lars and Marlow, Cameron %B = } %C = %D = 2011 %I = %T = The Anatomy of the Facebook Social Graph} %U = http://arxiv.org/abs/1111.4503

@article{hotho2010ubiquitous, author = {Hotho, Andreas and Ulslev Pedersen, Rasmus and Wurst, Michael}, title = {Ubiquitous Data}, journal = {Lecture Notes in Computer Science}, publisher = {Springer}, year = {2010}, number = {6202}, pages = {61--74}, url = {http://rd.springer.com/content/pdf/10.1007%2F978-3-642-16392-0_4.pdf}, issn = {0302-9743}, keywords = {2010, data, dm, mining, myown, social, ubiquitous} }

%0 = article %A = Hotho, Andreas and Ulslev Pedersen, Rasmus and Wurst, Michael %D = 2010 %I = Springer %T = Ubiquitous Data %U = http://rd.springer.com/content/pdf/10.1007%2F978-3-642-16392-0_4.pdf