| Περίληψη: | The Sharing Economy has been recently introduced as a new economic model in which physical resources or services are shared between private individuals, either free or for a fee. The arrangement of a sharing transaction is usually made among strangers, typically facilitated by Internet based on-line platforms.
This dissertation addresses consumer’s trust issues related to the emerging sharing economy model. It proposes an approach for measuring trust in the sharing economy model which is based on the estimation of the public sentiment as expressed in Twitter posts. After the presentation of trust conceptualization in the economic science, the dissertation focuses on the importance of trust in the economic model of sharing economy, where trust relationships must be established between strangers in virtual environments. An introduction to computational methods for representing trust in digital world, namely as reputation or feedback systems, along with the discussion of their well-known problems or biases, were followed by a literature review of Sentiment Analysis approaches for trust measurement. Unsupervised Sentiment Analysis methods were also used by this study for computing trust in the sharing economy model by mining opinions that were expressed in Twitter micro-blogging service.
More specifically, by using a simple function it was feasible to translate the general sentiment of tweets for the sharing economy as trust in the model. Simultaneously, time series analysis and predictive modeling were used for conducting a study for the levels and components of trust in sharing economy for the period 2010-2018.
The aim of this study was not only to measure whether consumers trust the model of the sharing economy, but also to examine trust in the two major players of this industry, Airbnb and Uber. Consequently, in this context, the dissertation examined the frequency of terms which coincidences with individual’s opinions categorized into positive and negative sentiments separately for each entity.
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