COVID-19 and tourism: extracting public attitudes

نویسندگانMahdi Hajiabadi,Hamideh Hajiabadi
نشریهCurrent Issues in Tourism
شماره صفحات547-553
شماره سریال26
شماره مجلد4
نوع مقالهFull Paper
تاریخ انتشار2023
نوع نشریهچاپی
کشور محل چاپایران
نمایه نشریهISI،JCR،Scopus

چکیده مقاله

Taking advantage of the users' posts on Twitter, we investigate the impact of COVID-19 on tourism in the early months of the epidemic. For this purpose, more than two million tweets published in the first months of the outbreak are analyzed. A comprehensive lexicon of keywords in the field of tourism, as well as international airlines, is collected and used for extracting tourism-related tweets. Employing a new model based on the RoBERTa language, we extract the sentiments of tweets for different countries. The results show differences in users' positive or negative views in different countries. While in some countries, such as Germany, the public view is positive, the public view is negative in other countries, such as Russia.

لینک ثابت مقاله

tags: Tourism, Sentiment Analysis, NLP, Knowledge extraction, COVID-19