Whether it is a beautiful house on the countryside or an inspiring chef who can serve stunning food at your home, now consumers can access and enjoy things that they were not able to afford previously. This is thanks to sharing economy, which, in only a decade, has experienced explosive growth. Given the rise of sharing platforms such as Uber or Airbnb, it feels as if purchasing goods is not as essential as before. In this project, accordingly, we investigate how the proliferation of sharing opportunities influences consumer decision making.
We propose to test this idea via a computerized text analysis on Twitter using machine learning methods. Students are expected to contribute in the content analysis of textual data and work on categorization of a representative sample of data according to a coding scheme. Students need to have interest in language use and applications of machine learning in consumer decision making.
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