Abstract
This study aims to quantify the sentiment of those discussing Airbnb on Twitter and visualise how this sentiment differed in three main periods: prior to the pandemic (pre-COVID-19), and during the pandemic before vaccines were disseminated (pre-vaccine), and during the pandemic, after vaccines were disseminated (post-vaccine). 344,705 tweets relating to Airbnb are collected. In this study, popularity, and usage analytics, sentiment analytics, voice analytics, and topic mining analytics were utilised. Through exploring the data in these three periods, it is possible to distinguish inverse correlations between the number of COVID-19 cases/deaths as compared to the popularity and positive sentiment of Airbnb-related tweets. Other findings include the topics most mentioned along with Airbnb on Twitter and an illustration of how the ‘voice’ of COVID-19 manifests in Airbnb tweets. The unique contribution of this study is in exploring Twitter sentiment towards Airbnb throughout the pandemic, as well as after the vaccine dissemination.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 124-154 |
| Number of pages | 31 |
| Journal | International Journal of Web Based Communities |
| Volume | 21 |
| Issue number | 1-2 |
| DOIs | |
| State | Published - 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Software
- Communication
- Education
- Computer Networks and Communications
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