Abstract
This chapter describes social media's role in understanding the impact of the COVID-19 pandemic on the tourism industry. At first, collecting large amounts of unstructured data from tourism-related digital media, social media, and search engines is explained. Then how these data can be analysed with artificial intelligence and machine learning-based sentiment analysis, content analysis, and topic modelling algorithms is described based on similar studies in the literature. Finally, how the collected data can be used to understand tourists' positive and negative experiences in the pandemic and determine their expectations from tourism enterprises, tourism-related public institutions, and government officials is expressed. Consequently, this chapter summarises how the digital world's big data resources can be used to extract knowledge about tourism during the pandemic.
TopBackground
Many studies have been conducted in the tourism sector on applying sentiment and content analysis to data collected from the digital world to understand customers' perceptions, thoughts, and expectations. As the first example of the studies conducted on this subject, researching tourists' perceptions of southern Italy's touristic region using Twitter social media data (Vecchio, 2017) can be given. In this study, the valuable information provided by the data obtained by collecting and analysing the posts on Twitter is mentioned. It has been stated that social media data can be used to provide better experiences to tourists and produce personalised marketing techniques.
Key Terms in this Chapter
Topic Modelling: The method for unsupervised classification of documents such as social media data, blog posts, news articles according to its' content.
Natural Language Processing (NLP): The process of using artificial intelligence tools to analyse the rules and structure of human languages to understand and analyse the meaning in the texts.
Content Analysis: The process of determining the categories or themes found in the content of a text.
Application User Interface (API): The interfaces used to provide interaction between different software and applications.
Sentiment Analysis: A text analysis approach that automatically determines the emotion and polarity (negative, positive, neutral) in a text.
Social Media Big Data Analytics: The process of obtaining knowledge by collecting and analysing social media data for a specific purpose.