Corpus ID: 221139364

Computational timeline reconstruction of the stories surrounding Trump: Story turbulence, narrative control, and collective chronopathy

@article{Dodds2020ComputationalTR,
  title={Computational timeline reconstruction of the stories surrounding Trump: Story turbulence, narrative control, and collective chronopathy},
  author={P. S. Dodds and J. R. Minot and M. Arnold and T. Alshaabi and J. L. Adams and A. J. Reagan and C. Danforth},
  journal={ArXiv},
  year={2020},
  volume={abs/2008.07301}
}
  • P. S. Dodds, J. R. Minot, +4 authors C. Danforth
  • Published 2020
  • Physics, Computer Science, History
  • ArXiv
  • Measuring the specific kind, temporal ordering, diversity, and turnover rate of stories surrounding any given subject is essential to developing a complete reckoning of that subject's historical impact. Here, we use Twitter as a distributed news and opinion aggregation source to identify and track the dynamics of the dominant day-scale stories around Donald Trump, the 45th President of the United States. Working with a data set comprising around 20 billion 1-grams, we first compare each day's 1… CONTINUE READING
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