| Περίληψη: | This dissertation examines the application of the method of Aspect-Oriented Sentiment Analysis in the field of shared economy. The importance of this study
arises from the significance of the concept of trust in the area of shared economy.
Since a service in sharing economy is not provided by an official body or business
but rather by individuals, the only means to secure future users is the experience
of the previous ones, as expressed through the reviews and comments they leave
on the corresponding platform. Consequently, such an environment provides the
ideal conditions for Sentiment Analysis, which can contribute to maximum safety
and quality of use to the users.
More specifically, this paper uses user reviews of the Airbnb property rental platform to determine their emotional attitude towards the properties where they
stayed, i.e. whether they were happy or not with their stay there. Their emotional
attitude is considered not only as a whole, but also in terms of a number
of pre-defined aspects regarding the services provided. In order to determine this
attitude, a process of non-supervised machine learning is followed, which focuses
on the definition of individual aspects of sentiment assessment as well as their
evaluation.
|
|---|
