Visual analysis of retweeting propagation network in a microblogging platform

  • Authors:

  • Quan Li;Huamin Qu;Li Chen;Robert Wang;Junhai Yong;Detan Si

  • Affiliations:

  • Tsinghua University;Hong Kong University of Science and Technology;Tsinghua University;Information System, Sina Technology, (China)Co., Ltd;Tsinghua University;Information System, Sina Technology, (China)Co., Ltd

  • Venue:
  • Proceedings of the 6th International Symposium on Visual Information Communication and Interaction
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

As a novel type of real-time social networking service, microblogging has already become ubiquitous and an irreplaceable tool. Tracking in the pulse of retweeting propagation is important and meaningful. In this paper, we investigate how information propagation in a specific microblogging platform evolves to identify relevant patterns and understand dynamic attributes of information propagation and the underlying sociological motivations. More specifically, based on the node-link diagram, we propose three efficient strategies to map the multiple attributes of information propagation graph to appropriate visual elements. For revealing the dynamic attributes, we propose two models: the depth-varying and the time-varying parallel data model to illustrate the temporal evolution efficiently. We also present a novel method by combining the traditional scatter plot with Hough transformation to represent the distribution of propagation instances and trace the propagation speeds. We integrate our methods to a visual mining tool and develop several interactive features. We demonstrate how our approaches improve the understanding of the propagation graph from a visual perspective by employing propagation datasets collected from Sina Weibo, the largest microblogging service provider in mainland China. Meanwhile, this visual mining tool has been evaluated by data analysts and successfully used in Sina Corporation as a helpful assistant to them.