Story explorer: A visual analysis tool for heterogeneous text data

@article{Wang2014StoryEA,
  title={Story explorer: A visual analysis tool for heterogeneous text data},
  author={Chenglong Wang and Zhengjie Miao and Siming Chen and Zipeng Liu and Zuchao Wang and Zhenhuang Wang and Xiaoru Yuan},
  journal={2014 IEEE Conference on Visual Analytics Science and Technology (VAST)},
  year={2014},
  pages={335-336}
}
We propose Story Explorer, a visual analytic system for text data from multiple sources. With various visualizations, our system can help analysts identify conflicts and correlations in large volume of text data, and detect patterns of group of people. Thus analysts can discover the development of events and find the suspicious people in the events.