title: CiteRivers: Visual Analytics of Citation Patterns.
abstract: The exploration and analysis of scientific literature collections is an important task for effective knowledge management. Past interest in such document sets has spurred the development of numerous visualization approaches for their interactive analysis. They either focus on the textual content of publications, or on document metadata including authors and citations. Previously presented approaches for citation analysis aim primarily at the visualization of the structure of citation networks and their exploration. We extend the state-of-the-art by presenting an approach for the interactive visual analysis of the contents of scientific documents, and combine it with a new and flexible technique to analyze their citations. This technique facilitates user-steered aggregation of citations which are linked to the content of the citing publications using a highly interactive visualization approach. Through enriching the approach with additional interactive views of other important aspects of the data, we support the exploration of the dataset over time and enable users to analyze citation patterns, spot trends, and track long-term developments. We demonstrate the strengths of our approach through a use case and discuss it based on expert user feedback.
authors.forename: Florian
authors.initials: F
authors.lastname: Heimerl
authors.forename: Qi
authors.initials: Q
authors.lastname: Han
authors.forename: Steffen
authors.initials: S
authors.lastname: Koch
authors.forename: Thomas
authors.initials: T
authors.lastname: Ertl