Prof. Dr. Felix Naumann

Joint Visualisation of Network and Text Data

Many large text collections exhibit graph structures, either inherent to the content itself or encoded in the metadata of the individual documents. Example graphs extracted from document collections are co-author networks, citation networks, or named-entity-cooccurrence networks. Furthermore, social networks can be extracted from email corpora, tweets, or social media. When it comes to visualising these large corpora, either the textual content or the network graph are used.

With MODiR (multi-objective dimensionality reduction), we propose to incorporate both, text and graph, to not only visualise the semantic information encoded in the documents' content but also the relationships expressed by the inherent network structure. To this end, we introduced a novel algorithm based on multi-objective optimisation to jointly position embedded documents and graph nodes in a two-dimensional landscape.


  • Visualising Large Documen... - Download
    Repke, T., Krestel, R. (2020) “Visualising Large Document Collections by Jointly Modeling Text and Network Structure”, Proceedings of the Joint Conference on Digital Libraries (JCDL).
  • Exploration Interface for... - Download
    Repke, T., Krestel, R. (2020) “Exploration Interface for Jointly Visualised Text and Graph Data”, International Conference on Intelligent User Interfaces Companion (IUI ’20).
  • Topic-aware Network Visua... - Download
    Repke, T., Krestel, R. (2018) “Topic-aware Network Visualisation to Explore Large Email Corpora”, International Workshop on Big Data Visual Exploration and Analytics (BigVis), Workshop Proceedings of the EDBT/ICDT 2018 Joint Conference.