When the storm is over: Sentiments, communities and information flow in the aftermath of Hurricane Dorian

Badmus, Oluwole Martins

doi:10.1016/j.ijdrr.2020.101645

Cited by 6 publications

(1 citation statement)

References 35 publications

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“…Specifically in situations of national or global concerns it has acted as a good source of information sharing. Social media analytics has been previously used to study the communication of natural disasters (Imran et al , 2015; Kryvasheyeu et al , 2016; Li et al , 2018; Wang and Ye, 2018; Wang et al , 2019), and some studies have also highlighted the impact that these disasters had on general public and their emotions (Badmus, 2020; Chen et al , 2020; Neppalli et al , 2017). But, there are only limited studies on COVID-19 and social media (Das and Dutta, 2020).…”

Section: Introductionmentioning

confidence: 99%

Decoding the global trend of “vaccine tourism” through public sentiments and emotions: does it get a nod on Twitter?

Gulati

2021

GKMC

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Purpose This paper aims to fill the major research gap prevalent in the tourism literature on the new form of tourism branching out from the COVID-19. While there are newspaper reports mentioning about the government’s reaction to vaccine tourism, there is no such study or report that tries to understand what the global masses feel about it; thus, a preliminary investigation of the social sentiment and emotion accruing around vaccine tourism on Twitter is carried out. Design/methodology/approach This exploratory study serves as a preliminary investigation of the social sentiment and emotion accruing around vaccine tourism on Twitter and tries to categorise them into eight basic emotions from Plutchik (1994) “wheel of emotions” as joy, disgust, fear, anger, anticipation, sadness, trust and surprise. The results are presented through data visualisation technique for analysis. The study makes use of R programming languages and the extensive packages offered on RStudio. Findings A total of 12,258 emotions were captured. It is evident that Vaccine Tourism has got maximum of positive sentiments (28.14%) which is almost double of the negative sentiment (14.05%). It is visible that the highest sentiment is “trust” (12.74%) and is followed by “fear” (8.97%). The least visible sentiment is “surprise” (4.32%). Polarity has been found for maximum tweets as positive (55.52%) which yet again surpasses negative polarity (33.7%), and neutral polarity is the least (10.67%). Research limitations/implications It can be said that people bear a positive emotion regarding vaccine tourism such as “trust” and “joy” which also denotes a positive sentiment score for testing polarity. But there are still concerns of high prices of the packages, fear-prevalent people to step out, and the uncertainty of right precautionary measures being taken still puts vaccine tourism under the radar of doubt with a fourth population having negative and neutral sentiments each. This is indicative with “fear” being the second highest emotion to the users. There are mixed emotions for vaccine tourism, but positive dominates the results. Practical implications The study attempts to see the global reaction on social media on vaccine tourism trend for giving food for thought to marketers. It can be said that Asians can be the target group. Originality/value To the best of the authors’ knowledge, there is no study that addresses the new trend of “Vaccine Tourism” or attempts to understand the emotions and sentiments of people globally.

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