IMDb Explorer: Visual Exploration of a Movie Database

ABSTRACT

Lots of movies are produced every year, too many to watch all of them and in particular, to get an overview about the evolution of typical movie genres and actors playing in them. Moreover, it is a challenging problem to detect correlations among the movies and the actors in those movies, in particular, if we are interested in time-varying data patterns like trends, countertrends, or anomalies and outliers. Those correlations are specifically interesting if they can be inspected on different levels of granularity, e.g., temporal, but also hierarchical in form of country- or continent-based correlations. In this paper we describe the IMDb Explorer, a web-based visualization tool that consists of two major views denoted by the movie cosmos and the career lines. Both views are linked and interactively manipulable while a list of user-defined metrics are explorable. We illustrate the usefulness of the visualization tool by applying it to the entire movie database provided by IMDb.

References

1. Wolfgang Aigner, Silvia Miksch, Heidrun Schumann, and Christian Tominski. 2011. Visualization of Time-Oriented Data. Springer.
2. Michael Burch, Felix Bott, Fabian Beck, and Stephan Diehl. 2008. Cartesian vs. Radial - A Comparative Evaluation of Two Visualization Tools. In Proceedings of the International Symposium on Advances in Visual Computing, ISVC. 151--160.
3. Michael Burch, Michael Fritz, Fabian Beck, and Stephan Diehl. 2010. TimeSpiderTrees: A Novel Visual Metaphor for Dynamic Compound Graphs. In Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC. 168--175.
4. Michael Burch, Benjamin Schmidt, and Daniel Weiskopf. 2013. A Matrix-Based Visualization for Exploring Dynamic Compound Digraphs. In Proceedings of the International Conference on Information Visualisation, IV. 66--73.
5. Michael Burch and Daniel Weiskopf. 2011. Visualizing Dynamic Quantitative Data in Hierarchies - TimeEdgeTrees: Attaching Dynamic Weights to Tree Edges. In IMAGAPP & IVAPP 2011 - Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications. 177--186.
6. William S. Cleveland and Robert McGill. 1986. An Experiment in Graphical Perception. International Journal of Man-Machine Studies 25, 5 (1986), 491--501.
7. Jochen Görtler, Christoph Schulz, Daniel Weiskopf, and Oliver Deussen. 2018. Bubble Treemaps for Uncertainty Visualization. IEEE Transactions on Visualization and Computer Graphics 24, 1 (2018), 719--728.
8. Dominique Haughton, Mark-David McLaughlin, Kevin Mentzer, and Changan Zhang. 2014. Movie analytics: Visualization of the co-starring network. In 4th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2014, Paris, France, November 9-10, 2014. 115--116.
9. Kuno Kurzhals, Brian D. Fisher, Michael Burch, and Daniel Weiskopf. 2014. Evaluating visual analytics with eye tracking. In Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization, BELIV. 61--69.
10. Col Needham. 2018. https://www.imdb.com/
11. Jonathan C. Roberts. 2007. State of the Art: Coordinated & Multiple Views in Exploratory Visualization. In Proceedings of Fifth International Conference on CMV. 61--71.
12. Ruth Rosenholtz, Yuanzhen Li, Jonathan Mansfield, and Zhenlan Jin. 2005. Feature congestion: a measure of display clutter. In Proceedings of the 2005 Conference on Human Factors in Computing Systems. 761--770.
13. B. Shneiderman. 1992. Tree Visualization with Tree-Maps: 2-D Space-Filling Approach. ACM Transactions on Graphics 11, 1 (1992), 92--99.
14. Ben Shneiderman. 1996. The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. In Proceedings of the IEEE Symposium on Visual Languages. 336--343.
15. Michail Vlachos and Daniel Svonava. 2013. Recommendation and visualization of similar movies using minimum spanning dendrograms. Information Visualization 12, 1 (2013), 85--101.

Index Terms

• Human-centered computing

  • Visualization

    • Visualization techniques