Mapping the Uncanny Valley (Fall - 2020)

Advisor: Keith Burghardt (Viterbi School of Engineering)
Students: Yuchen Zhang , Nai Cih Liou , Haripriya Dharmala , Sakshi Goel , Raveena Kshatriya

Description

While many stories involve the friendly and familiar, scary stories across cultures, from Hamlet to Yotsuya Kaidan to Siren Head involve beings that are almost—but not quite—human. Can these stories give us insight into the “nearly-human” uncanny valley? And are the most popular stories at the nadir of this valley? In this project we aim to explore the uncanny valley through analysis of several thousand stories posted on Reddit posted over a decade. These data contain stories that cross a range of topics, and include user comments and story scores. We will explore the prevalence of the monsters over time, and explore whether there is some optimal characteristics of these monsters that make them so scary. While some research has explored the uncanny valley for images, the research is limited and virtually unexplored in text format. The students will build on initial work by the advisor to apply NLP methods to these texts and improve upon existing initial results.

Awards

  • Best Cyberphysical Data Science Team

  • Highlighted Project

Students

Advisors

Skills Required by the team

  • Python
  • NLTK
  • NLP
  • Keras
  • Gensim
Fall 2020 Featured Best Cyberphysical Data Science Team Highlighted Project Ethics/Equity