PYXIDA Institutional Repository
and Digital Library
Collections :

Title :Topic modeling on AirBnB reviews during the pandemic
Alternative Title :Μοντελοποίηση θεμάτων σε κριτικές AirBnB κατά την πανδημία
Creator :Georgiou, Spyridon
Γεωργίου, Σπυρίδων
Contributor :Korfiatis, Nikolaos (Επιβλέπων καθηγητής)
Zachariadis, Emmanouil (Εξεταστής)
Lekakos, Georgios (Εξεταστής)
Athens University of Economics and Business, Department of Management Science and Technology (Degree granting institution)
Type :Text
Extent :62p.
Language :en
Identifier :
Abstract :In the current dissertation, we are going to exploit LDA topic models to analyze AirBnB online comments and discover meaningful patterns. Topic modelling is a well-known and prevalent tool to extract concepts of small or large text corpora. These text collections often enclose hidden meta groups. Valuable information on online reviews is often ignored, therefore our study will concentrate on extracting important and profitable business insights. Moreover, this research project aims to provide a clear understanding of how COVID-19 pandemic has influenced the tourism industry and how AirBnB has dealt with this unique and unfamiliar phenomenon. To be more precise, this analysis consists of gathering data from Get the Data - Inside AirBnB. Adding data to the debate. We will handle data from spring of 2020, which was the initial period that CoVID-19 affected Greece. Before applying LDA algorithm, we are going to implement preprocessing techniques. Preprocessing is the process of bringing your text into a form that is predictable and analyzable for your task, fitting it to a certain schema. After that, we will implement and train our model so that we obtain the results that will be evaluated.
Subject :AirBnB
Topic modelling
Μοντελοποίηση θεμάτων
Date Available :2021-09-08 20:06:21
Date Issued :2021
Date Submitted :2021-09-08 20:06:21
Access Rights :Free access
Licence :

File: Georgiou_2021.pdf

Type: application/pdf