28 citations · 199 across the 20 of their papers we have counts for
21 papers
Guided Graph Generation: Evaluation of Graph Generators in Terms of Network Statistics, and a New Algorithm
Jérôme Kunegis, Jun Sun, Eiko Yoneki
We consider the problem of graph generation guided by network statistics, i.e., the generation of graphs which have given values of various numerical measures that characterize net…
SynGraphy: Succinct Summarisation of Large Networks via Small Synthetic Representative Graphs
Jérôme Kunegis, Pawan Kumar, Jun Sun +2
We describe SynGraphy, a method for visually summarising the structure of large network datasets that works by drawing smaller graphs generated to have similar structural propertie…
Modeling the Evolution of Networks as Shrinking Structural Diversity
Jérôme Kunegis
This article reviews and evaluates models of network evolution based on the notion of structural diversity. We show that diversity is an underlying theme of three principles of net…
Understanding Social Networks using Transfer Learning
Jun Sun, Steffen Staab, Jérôme Kunegis
A detailed understanding of users contributes to the understanding of the Web's evolution, and to the development of Web applications. Although for new Web platforms such a study i…
'Dark Germany': Hidden Patterns of Participation in Online Far-Right Protests Against Refugee Housing
Sebastian Schelter, Jérôme Kunegis
The political discourse in Western European countries such as Germany has recently seen a resurgence of the topic of refugees, fueled by an influx of refugees from various Middle E…
Predicting User Roles in Social Networks using Transfer Learning with Feature Transformation
Jun Sun, Jérôme Kunegis, Steffen Staab
How can we recognise social roles of people, given a completely unlabelled social network? We present a transfer learning approach to network role classification based on feature t…
On the Ubiquity of Web Tracking: Insights from a Billion-Page Web Crawl
Sebastian Schelter, Jérôme Kunegis
We perform a large-scale analysis of third-party trackers on the World Wide Web from more than 3.5 billion web pages of the CommonCrawl 2012 corpus. We extract a dataset containing…
Continuous-Time Quantum Walks on Directed Bipartite Graphs
Beat Tödtli, Monika Laner, Jouri Semenov +3
This paper investigates continuous-time quantum walks on directed bipartite graphs based on a graph's adjacency matrix. We prove that on bipartite graphs, probability transport bet…
Linguistic neighbourhoods: explaining cultural borders on Wikipedia through multilingual co-editing activity
Anna Samoilenko, Fariba karimi, Daniel Edler +2
In this paper, we study the network of global interconnections between language communities, based on shared co-editing interests of Wikipedia editors, and show that although Engli…
Voting Behaviour and Power in Online Democracy: A Study of LiquidFeedback in Germany's Pirate Party
Christoph Carl Kling, Jerome Kunegis, Heinrich Hartmann +2
In recent years, political parties have adopted Online Delegative Democracy platforms such as LiquidFeedback to organise themselves and their political agendas via a grassroots app…
Social Networking by Proxy: A Case Study of Catster, Dogster and Hamsterster
Daniel Dünker, Jérôme Kunegis
The proliferation of online social networks in the last decade has not stopped short of pets, and many different online platforms now exist catering to owners of various pets such…
Exploiting the Structure of Bipartite Graphs for Algebraic and Spectral Graph Theory Applications
Jérôme Kunegis
In this article, we extend several algebraic graph analysis methods to bipartite networks. In various areas of science, engineering and commerce, many types of information can be r…
The Problem of Action at a Distance in Networks and the Emergence of Preferential Attachment from Triadic Closure
Jérôme Kunegis, Fariba Karimi, Jun Sun
In this paper, we characterise the notion of preferential attachment in networks as action at a distance, and argue that it can only be an emergent phenomenon -- the actual mechani…
DecLiNe -- Models for Decay of Links in Networks
Julia Preusse, Jérôme Kunegis, Matthias Thimm +1
The prediction of graph evolution is an important and challenging problem in the analysis of networks and of the Web in particular. But while the appearance of new links is part of…
Applications of Structural Balance in Signed Social Networks
Jérôme Kunegis
We present measures, models and link prediction algorithms based on the structural balance in signed social networks. Certain social networks contain, in addition to the usual 'fri…
Polcovar: Software for Computing the Mean and Variance of Subgraph Counts in Random Graphs
Jérôme Kunegis
The mean and variance of the number of appearances of a given subgraph in an Erdős--Rényi random graph over nodes are rational polynomials in . We present a piece of sof…
Handbook of Network Analysis [KONECT -- the Koblenz Network Collection]
Jérôme Kunegis
This is the handbook for the KONECT project, the \emph{Koblenz Network Collection}, a scientific project to collect, analyse, and provide network datasets for researchers in all re…
Preferential Attachment in Online Networks: Measurement and Explanations
Jérôme Kunegis, Marcel Blattner, Christine Moser
We perform an empirical study of the preferential attachment phenomenon in temporal networks and show that on the Web, networks follow a nonlinear preferential attachment model in…
On Joint Diagonalisation for Dynamic Network Analysis
Damien Fay, Jérôme Kunegis, Eiko Yoneki
Joint diagonalisation (JD) is a technique used to estimate an average eigenspace of a set of matrices. Whilst it has been used successfully in many areas to track the evolution of…
The Link Prediction Problem in Bipartite Networks
Jérôme Kunegis, Ernesto W. De Luca, Sahin Albayrak
We define and study the link prediction problem in bipartite networks, specializing general link prediction algorithms to the bipartite case. In a graph, a link prediction function…
The Universal Recommender
Jérôme Kunegis, Alan Said, Winfried Umbrath
We describe the Universal Recommender, a recommender system for semantic datasets that generalizes domain-specific recommenders such as content-based, collaborative, social, biblio…