Dr. Jérôme Kunegis
Latest blog entry: Largest Network Dataset Ever Released – As Big As Facebook
Note: German universities have two terms per year: a winter semester (WiSe – Wintersemester) and a summer semester (SoSe – Sommersemester).
- Network Theory and Dynamic Systems (in English), SoSe 2014
- Grundlagen der Datenbanken (Database Systems), WiSe 2013/2014
- Network Theory and Dynamic Systems (in English), SoSe 2013
- Proseminar "Soziale Netzwerke" (Social Networks), SoSe 2013
- Grundlagen der Datenbanken (Database Systems), WiSe 2012/2013
- Proseminar "Soziale Netzwerke" (Social Networks), SoSe 2012
- Grundlagen der Datenbanken (Database Systems), WiSe 2011/2012
- Grundlagen der Datenbanken (Database Systems), WiSe 2010/2011
- KONECT – Koblenz Network Collection
- Social Sensor – Sensing User-generated Input for Improved Media Discovery and Experience (EU FP7)
- KoMePol – Forschungsschwerpunkt "Kommunikation, Medien und Politik" (Communication, media, and politics)
- WeKnowIt – Emerging, Collective Intelligence for Personal, Organisational and Social Use (EU FP7)
- ROBUST – Risk and Opportunity Management of Huge-scale Business Community Cooperation (EU FP7)
- MULTIPLA – Crossing the Boundaries of Domains and Languages (DFG)
When I passed my PhD in Koblenz, my colleagues gave my a t-shirt that summarizes my research interests. On it was written "Everything is a Network". My research interests indeed follow these lines:
- Analysis of small and large networks
- I created the Koblenz Network Collection (KONECT) in order to have enough datasets to make significant research. KONECT is a collection of 180+ networks, and a Matlab toolbox for their analysis. I use KONECT for most of my research on networks. KONECT is growing constantly due to contributions from other researchers.
- Spectral and algebraic graph theory
- I have done much work on representing graphs as matrices and using the decomposition of these matrices to get insights on the graphs. My PhD thesis was about the use of graph matrix decompositions in link prediction. The main result of my PhD thesis is the Spectral Evolution Model.
- I showed how split-complex numbers can be used to model relationships on dating websites
- Modeling of complex networks
- Graphs with special structure
- I started my academic career with work on the Laplacian matrix for signed graphs. Later, I published one of the first online social network dataset with positive and negative edges: the Slashdot Zoo. On a higher level, I found out whether negative links are even necessary in social networks.
- I analysed more exotic matrix decompositions for directed networks.
- I analysed the special properties of bipartite networks.
- One of my long term research goal is to formulate a model of semantic networks
Other interests of me include:
- Web Science
- Beside being part of the Institute for Web Science and Technologies at the University of Koblenz–Landau, I have been involved with the organization of the Web Science Conference and related Web Science workshops, and am also involved on multiple projects in which aspects of social sciences play a role. I have also been present on the Web Science conference roster since 2011.
- Interestingness on Twitter
- Tensor decomposition and joint diagonalization
In my PhD thesis, I studied the spectral characteristics of large dynamic networks and formulate the spectral evolution model. The spectral evolution model applies to networks that evolve over time, and describes their spectral decompositions such as the eigenvalue and singular value decomposition. My main result is an interpretation of the spectrum and eigenvectors of networks in terms of global and local effects. I show empirically that the spectrum describes a network on the global level, whereas eigenvectors describe a network at the local level, and derive from this several new link prediction methods.
- Workshop on Metrics, Analysis and Tools for Online Community Management at INFORMATIK 2013
- INFORMATIK, 2013, Publicity Chair.
- Conf. on Web Science (WebSci), 2011, Publicity Chair.
- Special Session on Uncertainty in Network Mining (UNM) at the Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU), 2010, Technical Chair.
Jérôme Kunegis Institute for Web Science and Technologies Universität Koblenz Universitätsstraße 1 56070 Koblenz Germany