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The #MeToo Movement in the United States: Text Analysis of Early Twitter Conversations.

Sepideh ModrekBozhidar Chakalov
Published in: Journal of medical Internet research (2019)
These data illustrate that revelations shared went beyond acknowledgement of having experienced sexual harassment and often included vivid and traumatic descriptions of early life experiences of assault and abuse. These findings and methods underscore the value of content analysis, supported by novel machine learning methods, to improve our understanding of how widespread the revelations were, which likely amplified the spread and saliency of the #MeToo movement.
Keyphrases
  • early life
  • machine learning
  • mental health
  • big data
  • spinal cord injury
  • social media
  • electronic health record
  • artificial intelligence
  • smoking cessation
  • deep learning
  • intimate partner violence
  • advance care planning