Visual analysis of topic competition on social media

IEEE Transactions on Visualization and Computer Graphics

Volumn 19, Issue 12, 2013, Pages 2012-2021

  Xu, Panpan ^a   Wu, Yingcai ^b   Wei, Enxun ^c   Peng, Tai Quan ^d   Liu, Shixia ^b   Zhu, Jonathan J H ^e   Qu, Huamin ^a  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

^b MICROSOFT RESEARCH ASIA   (China)

^c SHANGHAI JIAO TONG UNIVERSITY   (China)

^d NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^e CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

agenda setting; information diffusion; information propagation; Social media visuaization; topic competition

Indexed keywords

AGENDA SETTINGS; INFORMATION DIFFUSION; INFORMATION DIFFUSION PROCESS; INFORMATION PROPAGATION; INTUITIVE UNDERSTANDING; PRESIDENTIAL ELECTION; SOCIAL MEDIA; TIMELINE VISUALIZATIONS;

COMPETITION; SOCIAL ASPECTS;

VISUALIZATION;

ALGORITHM; ARTICLE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER INTERFACE; DATA MINING; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SOCIAL MEDIA; UTILIZATION REVIEW; PROCEDURES; UTILIZATION;

ALGORITHMS; COMPUTER GRAPHICS; DATA MINING; IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOCIAL MEDIA; USER-COMPUTER INTERFACE;

EID: 84885393523     PISSN: 10772626     EISSN: None     Source Type: Journal    
DOI: 10.1109/TVCG.2013.221     Document Type: Article

References (50)

1. Project cascade. http://nytlabs.com/projects/cascade. html, Sept. 2011.
2. Revisit. http://moritz.stefaner.eu/projects/revisit/, Sept. 2012.
3. D. Archambault, D. Greene, P. Cunningham, and N. Hurley. Theme-Crowds: Multiresolution summaries of twitter usage. In Proceedings of the Workshop on Search and Mining User-generated Contents, pages 1-20, 2011.
4. S. Asur, B. A. Huberman, G. Szabo, and C. Wang. Trends in social media: Persistence and decay. In Proceedings of the International AAAI Conference on Weblogs and Social Media, pages 434-437, 2011.
5. M. Q. W. Baldonado, A. Woodruff, and A. Kuchinsky. Guidelines for using multiple views in information visualization. In Proceedings of Advanced Visual Interfaces, pages 110-119, 2000.
6. S. Boyd and L. Vandenberghe. Convex Optimization. Berichte ̈uber verteilte messysteme. Cambridge University Press, 2004.
7. L. Byron and M. Wattenberg. Stacked graphs-geometry & aesthetics. IEEE Transactions on Visualization and Computer Graphics, 14(6):1245-1252, 2008.
8. N. Cao, Y.-R. Lin, X. Sun, D. Lazer, S. Liu, and H. Qu. Whisper: Tracing the spatiotemporal process of information diffusion in real time. IEEE Transactions on Visualization and Computer Graphics, 18(12):2649-2658, 2012.
9. W. Cui, S. Liu, L. Tan, C. Shi, Y. Song, Z. Gao, H. Qu, and X. Tong. Textflow: Towards better understanding of evolving topics in text. IEEE Transactions on Visualization and Computer Graphics, 17(12):2412-2421, 2011.
10. N. Diakopoulos, M. Naaman, and F. Kivran-Swaine. Diamonds in the rough: Social media visual analytics for journalistic inquiry. In Proceedings of IEEE Symposium on Visual Analytics Science and Technology, pages 115-122, 2010.
11. M. D̈ork, D. Gruen, C.Williamson, and S. Carpendale. A visual backchannel for large-scale events. IEEE Transactions on Visualization and Computer Graphics, 16(6):1129-1138, 2010.
12. J. Durbin and G. S. Watson. Testing for serial correlation in least squares regression. Biometrika, 37(3/4):409-428, 1950.
13. D. Easley and J. Kleinberg. Networks, Crowds, and Markets: Reasoning About a Highly Connected World, volume 1. Cambridge University Press, 2010.
14. E. R. Gansner, Y. Hu, and S. C. North. Visualizing streaming text data with dynamic graphs and maps. In Proceedings of Graph Drawing, pages 439-450, 2012.
15. M. Gupta, J. Gao, Y. Sun, and J. Han. Integrating community matching and outlier detection for mining evolutionary community outliers. In Proceedings of the ACM SIGKDD international conference on Knowledgediscovery and data mining, pages 859-867, 2012.
16. S. Havre, E. Hetzler, P. Whitney, and L. Nowell. ThemeRiver: Visualizing thematic changes in large document collections. IEEE Transactions on Visualization and Computer Graphics, 8(1):9-20, 2002. (Pubitemid 34573479)
17. M. Hu, S. Liu, F. Wei, Y. Wu, J. Stasko, and K.-L. Ma. Breaking news on twitter. In ACM CHI, pages 2751-2754, 2012.
18. J. Johansson, P. Ljung, and M. Cooper. Depth cues and density in temporal parallel coordinates. In Proceedings of EuroVis, pages 35-42, 2007.
19. N. W. Kim, S. K. Card, and J. Heer. Tracing genealogical data with timenets. In Proceedings of Advanced Visual Interfaces, pages 241-248, 2010.
20. R. Kosara, F. Bendix, and H. Hauser. Time histograms for large, timedependent data. In Proceedings of EuroVis, pages 45-54, 2004.
21. S. Laxman and P. Sastry. A survey of temporal data mining. Sadhana, 31(2):173-198, 2006. (Pubitemid 43764855)
22. B. Lee, N. H. Riche, A. K. Karlson, and M. S. T. Carpendale. Sparkclouds: Visualizing trends in tag clouds. IEEE Transactions on Visualization and Computer Graphics, 16(6):1182-1189, 2010.
23. 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), 2013.
24. S. Liu, M. X. Zhou, S. Pan, Y. Song, W. Qian, W. Cai, and X. Lian. Tiara: Interactive, topic-based visual text summarization and analysis. ACM Transactions on Intelligent Systems and Technology, 3(2):25:1-25:28, Feb. 2012.
25. D. Luo, J. Yang, M. Krstajic, W. Ribarsky, and D. A. Keim. EventRiver: Visually exploring text collections with temporal references. IEEE Transactions on Visualization and Computer Graphics, 18(1):93-105, 2012.
26. A. Marcus, M. Bernstein, O. Badar, D. Karger, S. Madden, and R. Miller. Twitinfo: aggregating and visualizing microblogs for event exploration. In ACM CHI, pages 227-236, 2011.
27. M. Mccombs and J. Zhu. Capacity, diversity, and volatility of the public agenda: Trends from 1954 to 1994. Public Opinion Quarterly, 59(4):495-525, 1995. (Pubitemid 126027856)
28. M. E. McCombs and D. L. SHAW. The agenda-setting function of mass media. Public Opinion Quarterly, 36(2):176-187, 1972.
29. W. Muller and H. Schumann. Visualization methods for time-dependent data-an overview. In Proceedings of the Simulation Conference, volume 1, pages 737-745 Vol.1, 2003.
30. R. Munroe. Xkcd #657: Movie narrative charts. http://xkcd.com/657, December 2009.
31. S. Myers and J. Leskovec. Clash of the contagions: Cooperation and competition in information diffusion. In Proceedings of IEEE International Conference on Data Mining, pages 539-548, 2012.
32. M. Ogawa and K.-L. Ma. Software evolution storylines. In Proceedings of the international symposium on Software visualization, pages 35-42, 2010.
33. V. Ogievetsky. Plotweaver. http://ogievetsky.com/PlotWeaver/.
34. K. Reda, C. Tantipathananandh, A. E. Johnson, J. Leigh, and T. Y. Berger-Wolf. Visualizing the evolution of community structures in dynamic social networks. Computer Graphics Forum, 30(3):1061-1070, 2011.
35. S. Rose, S. Butner, W. Cowley, M. Gregory, and J. Walker. Describing story evolution from dynamic information streams. In Proceedings of IEEE Symposium on Visual Analytics Science and Technology, pages 99-106, 2009.
36. G. Salton, A. Wong, and C. S. Yang. A vector space model for automatic indexing. Commun. ACM, 18(11):613-620, Nov. 1975.
37. C. Shi, W. Cui, S. Liu, P. Xu, W. Chen, and H. Qu. RankExplorer: Visualization of ranking changes in large time series data. IEEE Transactions on Visualization and Computer Graphics, 18(12):2669-2678, 2012.
38. L. Shi, F. Wei, S. Liu, L. Tan, X. Lian, and M. X. Zhou. Understanding text corpora with multiple facets. In Proceedings of IEEE Symposium on Visual Analytics Science and Technology, pages 99-106, 2010.
39. Y. Tanahashi and K.-L. Ma. Design considerations for optimizing storyline visualizations. IEEE Transactions on Visualization and Computer Graphics, 18(12):2679-2688, 2012.
40. J. van Wijk and E. Van Selow. Cluster and calendar based visualization of time series data. In Proceedings of IEEE Symposium on Information Visualization, pages 4-9, 140, 1999.
41. F. Víegas, M. Wattenberg, J. Hebert, G. Borggaard, A. Cichowlas, J. Feinberg, J. Orwant, and C. Wren. Google+ ripples: A native visualization of information flow. In Proceedings of the international conference on World Wide Web, pages 1389-1398, 2013.
42. C. Ware. Information Visualization: Perception for Design (Interactive Technologies). Morgan Kaufmann, 1st edition, Feb. 2000.
43. M. Wattenberg and J. Kriss. Designing for social data analysis. IEEE Transactions on Visualization and Computer Graphics, 12(4):549-557, 2006. (Pubitemid 43824567)
44. M. Weber, M. Alexa, and W. Muller. Visualizing time-series on spirals. In Proceedings of IEEE Symposium on Information Visualization, pages 7-13, 2001. (Pubitemid 33099020)
45. L. Weng, a. Flammini, a. Vespignani, and F. Menczer. Competition among memes in a world with limited attention. Scientific reports, 2:335, Jan. 2012.
46. K. Wongsuphasawat and D. Gotz. Exploring flow, factors, and outcomes of temporal event sequences with the outflow visualization. IEEE Transactions on Visualization and Computer Graphics, 18(12):2659-2668, 2012.
47. D. K. Wright and M. D. Hinson. How blogs and social media are changing public relations and the way it is practiced. Public Relations Journal, 2(2):1-21, 2008.
48. F. Wu and B. A. Huberman. Novelty and collective attention. Proceedings of the National Academy of Sciences, 104(45):17599-17601, 2007. (Pubitemid 350210881)
49. S. Wu, J. M. Hofman, W. A. Mason, and D. J. Watts. Who says what to whom on twitter. In Proceedings of the international conference on World Wide Web, pages 705-714, 2011.
50. J. Zhu. Issue competition and attention distraction: A zero-sum theory of agenda-setting. Journalism & Mass Communication Quarterly, 69(4):825-836, 1992.