Designing a Crowdsourcing Tool to Measure Perceived Causal Relationships Between Narrative Events

Abstract

The computational study of narrative is important to multiple academic disciplines. However, prior research has been limited by the inability to quantify subjects’ comprehension of the causal structure within each narrative text. With the aid of big data technology and crowdsourcing tools, we aim to design a new approach to analysis 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 tool that can be used to measure people’s understanding of the causal relationships within a piece of text.