Visual Analysis of Topic Competition on Social Media

被引：109

作者：

Xu, Panpan ^{[1
]}

Wu, Yingcai ^{[2
]}

Wei, Enxun ^{[3
]}

Peng, Tai-Quan ^{[4
]}

Liu, Shixia ^{[2
]}

Zhu, Jonathan J. H.

Qu, Huamin ^{[1
]}

机构：

[1] Hong Kong Univ Sci & Technol, Hong Kong, Hong Kong, Peoples R China

[2] Shanghai Jiao Tong Univ, Shanghai 200030, Peoples R China

[3] Nanyang Technol Univ, Singapore, Singapore

[4] City Univ Hong Kong, Hong Kong, Hong Kong, Peoples R China

来源：

IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS | 2013年 / 19卷 / 12期

关键词：

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

D O I：

10.1109/TVCG.2013.221

中图分类号：

TP31 [计算机软件];

学科分类号：

081205 [计算机软件];

摘要：

How do various topics compete for public attention when they are spreading on social media? What roles do opinion leaders play in the rise and fall of competitiveness of various topics? In this study, we propose an expanded topic competition model to characterize the competition for public attention on multiple topics promoted by various opinion leaders on social media. To allow an intuitive understanding of the estimated measures, we present a timeline visualization through a metaphoric interpretation of the results. The visual design features both topical and social aspects of the information diffusion process by compositing ThemeRiver with storyline style visualization. ThemeRiver shows the increase and decrease of competitiveness of each topic. Opinion leaders are drawn as threads that converge or diverge with regard to their roles in influencing the public agenda change over time. To validate the effectiveness of the visual analysis techniques, we report the insights gained on two collections of Tweets: the 2012 United States presidential election and the Occupy Wall Street movement.

引用

页码：2012 / 2021

页数：10

共 50 条

[1]

Project Cascade, (2011)

[2]

(2012)

[3]

Archambault D., Greene D., Cunningham P., Hurley N., Theme-Crowds: Multiresolution summaries of twitter usage, Proceedings of the Workshop on Search and Mining User-generated Contents, pp. 1-20, (2011)

[4]

Asur S., Huberman B.A., Szabo G., Wang C., Trends in social media: Persistence and decay, Proceedings of the International AAAI Conference on Weblogs and Social Media, pp. 434-437, (2011)

[5]

Baldonado M.Q.W., Woodruff A., Kuchinsky A., Guidelines for using multiple views in information visualization, Proceedings of Advanced Visual Interfaces, pp. 110-119, (2000)

[6]

Boyd S., Vandenberghe L., Convex Optimization, (2004)

[7]

Byron L., Wattenberg M., Stacked graphs-geometry & aesthetics, IEEE Transactions on Visualization and Computer Graphics, 14, 6, pp. 1245-1252, (2008)

[8]

Cao N., Lin Y.-R., Sun X., Lazer D., Liu S., Qu H., Whisper: Tracing the spatiotemporal process of information diffusion in real time, IEEE Transactions on Visualization and Computer Graphics, 18, 12, pp. 2649-2658, (2012)

[9]

Cui W., Liu S., Tan L., Shi C., Song Y., Gao Z., Qu H., Tong X., Textflow: Towards better understanding of evolving topics in text, IEEE Transactions on Visualization and Computer Graphics, 17, 12, pp. 2412-2421, (2011)

[10]

Diakopoulos N., Naaman M., Kivran-Swaine F., Diamonds in the rough: Social media visual analytics for journalistic inquiry, Proceedings of IEEE Symposium on Visual Analytics Science and Technology, pp. 115-122, (2010)

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