A Computational Approach to Perceived Trustworthiness of Airbnb Host Profiles

Authors

  • Xiao Ma Jacobs Technion-Cornell Institute
  • Trishala Neeraj Jacobs Technion-Cornell Institute
  • Mor Naaman Jacobs Technion-Cornell Institute

Abstract

We developed a novel computational framework to predict the perceived trustworthiness of host profile texts in the context of online lodging marketplaces. To achieve this goal, we developed a dataset of 4,180 Airbnb host profiles annotated with perceived trustworthiness. To the best of our knowledge, the dataset along with our models allow for the first computational evaluation of perceived trustworthiness of textual profiles, which are ubiquitous in online peer-to-peer marketplaces. We provide insights into the linguistic factors that contribute to higher and lower perceived trustworthiness for profiles of different lengths.

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Published

2017-05-03

How to Cite

Ma, X., Neeraj, T., & Naaman, M. (2017). A Computational Approach to Perceived Trustworthiness of Airbnb Host Profiles. Proceedings of the International AAAI Conference on Web and Social Media, 11(1), 604-607. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/14937