Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2017

Santos Tiago, Walk Simon, Helic Denis

Nonlinear Characterization of Activity Dynamics in Online Collaboration Websites

WWW '17 Companion Proceedings of the 26th International Conference on World Wide Web Companion, International World Wide Web Conferences Steering Committee, Perth, Australia, 2017

Konferenz
Modeling activity in online collaboration websites, such asStackExchange Question and Answering portals, is becom-ing increasingly important, as the success of these websitescritically depends on the content contributed by its users. Inthis paper, we represent user activity as time series and per-form an initial analysis of these time series to obtain a bet-ter understanding of the underlying mechanisms that governtheir creation. In particular, we are interested in identifyinglatent nonlinear behavior in online user activity as opposedto a simpler linear operating mode. To that end, we applya set of statistical tests for nonlinearity as a means to char-acterize activity time series derived from 16 different onlinecollaboration websites. We validate our approach by com-paring activity forecast performance from linear and nonlin-ear models, and study the underlying dynamical systems wederive with nonlinear time series analysis. Our results showthat nonlinear characterizations of activity time series helpto (i) improve our understanding of activity dynamics in on-line collaboration websites, and (ii) increase the accuracy offorecasting experiments.
2016

Stanisavljevic Darko, Hasani-Mavriqi Ilire, Lex Elisabeth, Strohmaier M., Helic Denis

Semantic Stability in Wikipedia

Complex Networks and their Applications, Cherifi, H., Gaito, S., Quattrociocchi, W., Sala, A., Springer International Publishing AG, Cham, Switzerland, 2016

Konferenz
In this paper we assess the semantic stability of Wikipedia by investigat-ing the dynamics of Wikipedia articles’ revisions over time. In a semantically stablesystem, articles are infrequently edited, whereas in unstable systems, article contentchanges more frequently. In other words, in a stable system, the Wikipedia com-munity has reached consensus on the majority of articles. In our work, we measuresemantic stability using the Rank Biased Overlap method. To that end, we prepro-cess Wikipedia dumps to obtain a sequence of plain-text article revisions, whereaseach revision is represented as a TF-IDF vector. To measure the similarity betweenconsequent article revisions, we calculate Rank Biased Overlap on subsequent termvectors. We evaluate our approach on 10 Wikipedia language editions includingthe five largest language editions as well as five randomly selected small languageeditions. Our experimental results reveal that even in policy driven collaborationnetworks such as Wikipedia, semantic stability can be achieved. However, there aredifferences on the velocity of the semantic stability process between small and largeWikipedia editions. Small editions exhibit faster and higher semantic stability than large ones. In particular, in large Wikipedia editions, a higher number of successiverevisions is needed in order to reach a certain semantic stability level, whereas, insmall Wikipedia editions, the number of needed successive revisions is much lowerfor the same level of semantic stability.
2015

Hasani-Mavriqi Ilire, Geigl Florian, Pujari Subhash Chandra, Lex Elisabeth, Helic Denis

Influence of Status Social on Consensus Building in Collaboration Networks

In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2015), Jian Pei, Fabrizio Silvestri and Jie Tang, ACM/IEEE, Paris, France, 2015

Konferenz
In this paper, we analyze the influence of socialstatus on opinion dynamics and consensus building in collaborationnetworks. To that end, we simulate the diffusion of opinionsin empirical collaboration networks by taking into account boththe network structure and the individual differences of peoplereflected through their social status. For our simulations, weadapt a well-known Naming Game model and extend it withthe Probabilistic Meeting Rule to account for the social statusof individuals participating in a meeting. This mechanism issufficiently flexible and allows us to model various situations incollaboration networks, such as the emergence or disappearanceof social classes. In this work, we concentrate on studyingthree well-known forms of class society: egalitarian, ranked andstratified. In particular, we are interested in the way these societyforms facilitate opinion diffusion. Our experimental findingsreveal that (i) opinion dynamics in collaboration networks isindeed affected by the individuals’ social status and (ii) thiseffect is intricate and non-obvious. In particular, although thesocial status favors consensus building, relying on it too stronglycan slow down the opinion diffusion, indicating that there is aspecific setting for each collaboration network in which socialstatus optimally benefits the consensus building process.
2012

Helic Denis, Körner C., Granitzer Michael, Strohmaier M., Trattner Christoph

Navigational efficiency of broad vs. narrow folksonomies

In Proceedings of the 23rd Conference on Hypertext and Social Media (HT2012). ACM, 2012, 2012

Konferenz
Although many social tagging systems share a common tripartitegraph structure, the collaborative processes that aregenerating these structures can differ significantly. For example,while resources on Delicious are usually tagged by allusers who bookmark the web page cnn.com, photos on Flickrare usually tagged just by a single user who uploads thephoto. In the literature, this distinction has been describedas a distinction between broad vs. narrow folksonomies.This paper sets out to explore navigational differences betweenbroad and narrow folksonomies in social hypertextualsystems. We study both kinds of folksonomies on a datasetprovided by Mendeley - a collaborative platform where userscan annotate and organize scientific articles with tags. Ourexperiments suggest that broad folksonomies are more usefulfor navigation, and that the collaborative processes thatare generating folksonomies matter qualitatively. Our findingsare relevant for system designers and engineers aimingto improve the navigability of social tagging systems.
2011

Helic Denis, Strohmaier M., Trattner Christoph, Muhr M., Lerman K.

Pragmatic Evaluation of Folksonomies

20th International World Wide Web Conference (WWW2011), 2011

Konferenz
2011

Shahzad Syed K, Granitzer Michael, Helic Denis

Ontological Model Driven GUI Development: User Interface Ontology Approach

6th International Conference on Computer Sciences and Convergence Information Technology (ICCIT), IEEE, 2011

Konferenz
Ontology and Semantic Framework has becomepervasive in computer science. It has huge impact at database,business logic and user interface for a range of computerapplications. This framework is also being introduced, presentedor plugged at user interfaces for various software and websites.However, establishment of structured and standardizedontological model based user interface development environmentis still a challenge. This paper talks about the necessity of such anenvironment based on User Interface Ontology (UIO). To explorethis phenomenon, this research focuses at the User Interfaceentities, their semantics, uses and relationships among them. Thefirst part focuses on the development of User Interface Ontology.In the second step, this ontology is mapped to the domainontology to construct a User Interface Model. Finally, theresulting model is quantified and instantiated for a user interfacedevelopment to support our framework. This UIO is anextendable framework that allows defining new sub-conceptswith their ontological relationships and constraints.
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