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TopicWave: visual exploration for topics with hierarchical time-varying data

Published:05 January 2017Publication History

ABSTRACT

Opinion leaders have great influence in social networks. When influential events occur, experts may be concerned with the opinion flow of the event from social networks. Therefore, the trend of events during a time interval should be explored using a specific visualization tool. However, designing an intuitive and interactive visualization tool from a time-varying data is still a challenge. For example, major topics are commonly edited by opinion leaders on social networks, and people attracted by opinion leaders join the discussion by commenting on the post. This process is involved in hierarchical-level commentary, which increases/decreases in volume with time. Nevertheless, exploring commentary properties using traditional visualization techniques is also a challenge for users. In this paper, we propose TopicWave, a visualization tool that combines ThemeRiver Graph (time-varying visualization) and Sunburst (hierarchical data visualization) to visualize the trend of comments on a post in Facebook. TopicWave can also clearly present hierarchy and time-varying trend of comments on a Facebook fan page and provide an intuitive and interactive visualization design.

References

  1. W. Aigner, S. Miksch, H. Schumann, and C. Tominski. Visualization of Time-Oriented Data. Springer Publishing Company, Incorporated, 1st edition, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. L. Byron and M. Wattenberg. Stacked graphs - geometry & aesthetics. IEEE Transactions on Visualization and Computer Graphics, 14(6):1245--1252, Nov. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. W. Cui, S. Liu, Z. Wu, and H. Wei. How hierarchical topics evolve in large text corpora. IEEE transactions on visualization and computer graphics, 20(12):2281--2290, 2014.Google ScholarGoogle Scholar
  4. W. Dou, L. Yu, X. Wang, Z. Ma, and W. Ribarsky. Hierarchicaltopics: Visually exploring large text collections using topic hierarchies. IEEE Transactions on Visualization and Computer Graphics, 19(12):2002--2011, Dec 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Y.-S. Hwang, D.-H. Shin, and Y. Kim. Structural change in search engine news service: a social network perspective. Asian Journal of Communication, 22(2):160--178, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  6. B. Johnson and B. Shneiderman. Tree-maps: A space-filling approach to the visualization of hierarchical information structures. In Visualization, 1991. Visualization'91, Proceedings., IEEE Conference on, pages 284--291. IEEE, 1991. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. B. Kondo and C. Collins. Dimpvis: Exploring time-varying information visualizations by direct manipulation. IEEE Trans. on Visualization and Computer Graphics (Proc. of the IEEE Conf. on Information Visualization), 20(12), Dec. 2014.Google ScholarGoogle ScholarCross RefCross Ref
  8. S. Kriglstein, M. Pohl, and C. Stachl. Animation for time-oriented data: An overview of empirical research. In 2012 16th International Conference on Information Visualisation, pages 30--35. IEEE, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. J.-G. Lee, K. C. Lee, and D.-H. Shin. A new approach to exploring spatiotemporal space in the context of social network services. In International Conference on Social Computing and Social Media, pages 221--228. Springer, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. S. Liu, Y. Wu, E. Wei, M. Liu, and Y. Liu. Storyflow: Tracking the evolution of stories. IEEE Transactions on Visualization and Computer Graphics, 19(12):2436--2445, Dec 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. A. Rind, T. Lammarsch, W. Aigner, B. Alsallakh, and S. Miksch. Timebench: A data model and software library for visual analytics of time-oriented data. IEEE Transactions on Visualization and Computer Graphics, 19(12):2247--2256, Dec 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. M. Rubinstein, D. Gutierrez, O. Sorkine, and A. Shamir. A comparative study of image retargeting. In ACM transactions on graphics (TOG), volume 29, page 160. ACM, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. J. M. Rzeszotarski and A. Kittur. Kinetica: naturalistic multi-touch data visualization. In Proceedings of the 32nd annual ACM conference on Human factors in computing systems, pages 897--906. ACM, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. D.-H. Shin and D. Ahn. Associations between game use and cognitive empathy: A cross-generational study. Cyberpsychology, behavior, and social networking, 16(8):599--603, 2013.Google ScholarGoogle Scholar
  15. J. Stasko, R. Catrambone, M. Guzdial, and K. McDonald. An evaluation of space-filling information visualizations for depicting hierarchical structures. International journal of human-computer studies, 53(5):663--694, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. J. Stasko and E. Zhang. Focus+ context display and navigation techniques for enhancing radial, space-filling hierarchy visualizations. In Information Visualization, 2000. InfoVis 2000. IEEE Symposium on, pages 57--65. IEEE, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. J. J. Van Wijk and H. Van de Wetering. Cushion treemaps: Visualization of hierarchical information. In Information Visualization, 1999.(Info Vis' 99) Proceedings. 1999 IEEE Symposium on, pages 73--78. IEEE, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. X. Wang, S. Liu, Y. Song, and B. Guo. Mining evolutionary multi-branch trees from text streams. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 722--730. ACM, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. M. Wattenberg. Visualizing the stock market. In CHI'99 extended abstracts on Human factors in computing systems, pages 188--189. ACM, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. P. Xu, Y. Wu, E. Wei, T.-Q. Peng, S. Liu, J. J. Zhu, and H. Qu. Visual analysis of topic competition on social media. IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE VAST 2013, 19(12):2012--2021, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. D. Zhang, C. Zhai, and J. Han. Topic cube: Topic modeling for olap on multidimensional text databases. In SDM, volume 9, pages 1124--1135. SIAM, 2009.Google ScholarGoogle Scholar

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    • Published in

      cover image ACM Conferences
      IMCOM '17: Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication
      January 2017
      746 pages
      ISBN:9781450348881
      DOI:10.1145/3022227

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      Publication History

      • Published: 5 January 2017

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      IMCOM '17 Paper Acceptance Rate113of366submissions,31%Overall Acceptance Rate213of621submissions,34%
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