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.

Recent research advances on interactive machine learning

“…Thus, visual cluster analysis has been applied to many data-driven applications such as weather ensemble forecast (Kumpf et al, 2018) and air traffic optimization (Andrienko et al, 2018). Recent work mainly focuses on cluster-based exploratory data analysis (Andrienko et al, 2018;Badam et al, 2017;Heimerl et al, 2016;Sacha et al, 2018;Wu et al, 2017b,c), comparative clustering analysis (Jarema et al, 2015;Kumpf et al, 2018;Kwon et al, 2018;Zhang et al, 2016b), and bi-cluster analysis (Sun et al, 2016;Watanabe et al, 2015;Wu et al, 2017aWu et al, , 2015Zhao et al, 2018).…”

Topic Tomographies (TopTom): a visual approach to distill information from media streams

“…A common approach is to develop a main visualization for the overall perspective, then providing details adding information through interaction. Usually the combination of elements on multiple panels on the interface might create an information overload [ZCW∗14,DYW∗13,CLT∗11,HHKE16]. TopTom improves the interaction flow keeping only elements essential to the users and focusing on views connections.…”

Gram

“…In all these cases, the methodology proposed is demonstrated on only a small, well-defined corpus. Other examples of limited application of topic extraction include: computer science conferences and journals from the DLPB database [23], trends in computer science research [20], and publications in data visualization [28]. Graph visualization: Graph drawing libraries and toolkits make it easy for a graph to be visualized (e.g., GraphViz [5], OGDF [18], MSAGL [33], and VTK [38]); few of these support interaction or navigation -features essential for exploration of large graphs.…”