ABSTRACT
Video clickstream data are important for understanding user behaviors and improving online video services. Various visual analytics techniques have been proposed to explore patterns in these data. However, those techniques are mainly developed for analysis and do not sufficiently support presentations. It is still difficult for data analysts to convey their findings to an audience without prior knowledge. In this paper, we propose to use animated narrative visualization to present video clickstream data. Compared with traditional methods which directly turn click events into animations, our animated narrative visualization focuses on conveying the patterns in the data to a general audience and adopts two novel designs, non-linear time mapping and foreshadowing, to make the presentation more engaging and interesting. Our non-linear time mapping method keeps the interesting parts as the focus of the animation while compressing the uninteresting parts as the context. The foreshadowing techniques can engage the audience and alert them to the events in the animation. Our user study indicates the effectiveness of our system and provides guidelines for the design of similar systems.
- Aguiar, E., Nagrecha, S., and Chawla, N. V. 2015. Predicting online video engagement using clickstreams. In Data Science and Advanced Analytics (DSAA), 2015. 36678 2015. IEEE International Conference on, IEEE, 1--10.Google Scholar
- Aigner, W., Miksch, S., Müller, W., Schumann, H., and Tominski, C. 2007. Visualizing time-oriented dataa systematic view. Computers & Graphics 31, 3, 401--409. Google ScholarDigital Library
- Amini, F., Henry Riche, N., Lee, B., Hurter, C., and Irani, P. 2015. Understanding data videos: Looking at narrative visualization through the cinematography lens. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, ACM, 1459--1468. Google ScholarDigital Library
- Bach, B., Pietriga, E., and Fekete, J.-D. 2014. Graphdiaries: animated transitions andtemporal navigation for dynamic networks. Visualization and Computer Graphics, IEEE Transactions on 20, 5, 740--754. Google ScholarDigital Library
- Beal, C. R., and Cohen, P. R. 2008. Temporal data mining for educational applications. In PRICAI 2008: Trends in Artificial Intelligence. Springer, 66--77. Google ScholarDigital Library
- Bordwell, D., Thompson, K., and Ashton, J. 1997. Film art: An introduction, vol. 7. McGraw-Hill New York.Google Scholar
- Chorianopoulos, K. 2013. Collective intelligence within web video. Human-centric Computing and Information Sciences 3, 1, 1--16.Google ScholarCross Ref
- Dachselt, R., and Weiland, M. 2006. Timezoom: a flexible detail and context timeline. In CHI'06 Extended Abstracts on Human Factors in Computing Systems, ACM, 682--687. Google ScholarDigital Library
- Dragicevic, P., Bezerianos, A., Javed, W., Elmqvist, N., and Fekete, J.-D. 2011. Temporal distortion for animated transitions. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM, 2009--2018. Google ScholarDigital Library
- Foreshadowing.org, 2016. Types of foreshadowing. http://foreshadowing.org/types-of-foreshadowing.html. Retrived on April 27th, 2016.Google Scholar
- Fulda, J., Brehmer, M., and Munzner, T. 2016. Time-linecurator: Interactive authoring of visual timelines from unstructured text. Visualization and Computer Graphics, IEEE Transactions on 22, 1, 300--309.Google ScholarDigital Library
- Gratzl, S., Lex, A., Gehlenborg, N., Cosgrove, N., and Streit, M. 2016. From visual exploration to storytelling and back again. bioRxiv, 049585.Google Scholar
- Heer, J., and Robertson, G. G. 2007. Animated transitions in statistical data graphics. Visualization and Computer Graphics, IEEE Transactions on 13, 6, 1240--1247. Google ScholarDigital Library
- Hou, X., and Zhang, L. 2007. Saliency detection: A spectral residual approach. In Computer Vision and Pattern Recognition, 2007. CVPR'07. IEEE Conference on, IEEE, 1--8.Google Scholar
- Huron, S., Vuillemot, R., and Fekete, J.-D. 2013. Visual sedimentation. Visualization and Computer Graphics, IEEE Transactions on 19, 12, 2446--2455. Google ScholarDigital Library
- Lee, J., Podlaseck, M., Schonberg, E., and Hoch, R. 2001. Visualization and analysis of clickstream data of online stores for understanding web merchandising. In Applications of Data Mining to Electronic Commerce. Springer, 59--84. Google ScholarDigital Library
- McKee, R. 1997. Substance, Structure, Style, and the Principles of Screenwriting. New York: HarperCollins.Google Scholar
- Mediacollege, 2016. Manipulating time in video production. http://www.mediacollege.com/video/editing/. Retrieved on March 10th, 2016.Google Scholar
- Montgomery, A. L., Li, S., Srinivasan, K., and Liechty, J. C. 2004. Modeling online browsing and path analysis using clickstream data. Marketing Science 23, 4, 579--595.Google ScholarDigital Library
- Nguyen, P. H., Xu, K., Walker, R., and Wong, B. 2014. Schemaline: Timeline visualization for sensemaking. In Information Visualisation (IV), 2014 18th International Conference on, IEEE, 225--233.Google Scholar
- Riedl, M. O., and Young, R. M. 2010. Narrative planning: Balancing plot and character. Journal of Artificial Intelligence Research 39, 1, 217--268. Google ScholarDigital Library
- Robertson, G., Fernandez, R., Fisher, D., Lee, B., and Stasko, J. 2008. Effectiveness of animation in trend visualization. Visualization and Computer Graphics, IEEE Transactions on 14, 6, 1325--1332. Google ScholarDigital Library
- Rosling, H. 2009. Gapminder. GapMinder Foundation http://www.gapminder.org, 91.Google Scholar
- Segel, E., and Heer, J. 2010. Narrative visualization: Telling stories with data. Visualization and Computer Graphics, IEEE Transactions on 16, 6, 1139--1148. Google ScholarDigital Library
- Shi, C., Fu, S., Chen, Q., and Qu, H. 2015. Vismooc: Visualizing video clickstream data from massive open online courses. In Visualization Symposium (PacificVis), 2015 IEEE Pacific, IEEE, 159--166.Google Scholar
- Sigovan, C., Muelder, C. W., and Ma, K.-L. 2013. Visualizing large-scale parallel communication traces using a particle animation technique. In Computer Graphics Forum, vol. 32, Wiley Online Library, 141--150. Google ScholarDigital Library
- Thomas, F., Johnston, O., and Thomas, F. 1995. The illusion of life: Disney animation. Hyperion New York.Google Scholar
- Tversky, B., Morrison, J. B., and Betrancourt, M. 2002. Animation: can it facilitate? International journal of humancomputer studies 57, 4, 247--262. Google ScholarDigital Library
- Waldner, M., Le Muzic, M., Bernhard, M., Purgathofer, W., and Viola, I. 2014. Attractive flicker - guiding attention in dynamic narrative visualizations. Visualization and Computer Graphics, IEEE Transactions on 20, 12, 2456--2465.Google Scholar
- Wei, J., Shen, Z., Sundaresan, N., and Ma, K.-L. 2012. Visual cluster exploration of web clickstream data. In Visual Analytics Science and Technology (VAST), 2012 IEEE Conference on, IEEE, 3--12. Google ScholarDigital Library
- Zhao, J., Drucker, S. M., Fisher, D., and Brinkman, D. 2012. Timeslice: Interactive faceted browsing of timeline data. In Proceedings of the International Working Conference on Advanced Visual Interfaces, ACM, 433--436. Google ScholarDigital Library
Index Terms
- Animated narrative visualization for video clickstream data
Recommendations
Narrative Visualization: Telling Stories with Data
Data visualization is regularly promoted for its ability to reveal stories within data, yet these “data stories” differ in important ways from traditional forms of storytelling. Storytellers, especially online journalists, have increasingly been ...
A Deeper Understanding of Sequence in Narrative Visualization
Conveying a narrative with visualizations often requires choosing an order in which to present visualizations. While evidence exists that narrative sequencing in traditional stories can affect comprehension and memory, little is known about how ...
Understanding Data Videos: Looking at Narrative Visualization through the Cinematography Lens
CHI '15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing SystemsData videos, motion graphics that incorporate visualizations about facts, are increasingly gaining popularity as a means of telling stories with data. However, very little is systematically recorded about (a) what elements are featured in data videos ...
Comments