Measuring Perceived Causal Relationships Between Narrative Events with a Crowdsourcing Application on Mturk

  • Dian HuEmail author
  • David A. Broniatowski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10354)


The computational study of narrative is important to multiple academic disciplines. However, prior research has been limited by the inability to quantify each subject’s comprehension of the causal structure. With the aid of big data technology and crowdsourcing tools, we aim to design a new approach to analyze the content of narratives in a data-driven manner, while also making these analyses scientifically replicable. The goal of this research is therefore to develop a method that can be used to measure people’s understanding of the causal relationships within a piece of text.


Crowdsourcing Narrative Network Causal relationships 


Acknowledgment and Disclaimer

This work was supported in part by the National Institute of General Medical Sciences under grant number 5R01GM114771. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Engineering Management and Systems EngineeringThe George Washington UniversityWashington, DCUSA

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