ABSTRACT
Vaccination has been a hot topic in the present COVID-19 context. The government, public health stakeholders and media are all concerned about how to get the people vaccinated. The study was intended to explore the perception and emotions of the Indians citizens toward COVID-19 vaccine from Twitter messages. The tweets were collected for the period of 6 months, from mid-January to June, 2021 using hash-tags and keywords specific to India. Topics and emotions from the tweets were extracted using Latent Dirichlet Allocation (LDA) method and National Research Council (NRC) Lexicon, respectively. Theme, sentiment and emotion wise engagement and reachability metrics were assessed. Hash-tag frequency of COVID-19 vaccine brands were also identified and evaluated. Information regarding 'Co-WIN app and availability of vaccine' was widely discussed and also received highest engagement and reachability among Twitter users. Among the various emotions, trust was expressed the most, which highlights the acceptance of vaccines among the Indian citizens. The hash-tags frequency of vaccine brands shows that Covishield was popular in the month of March 2021, and Covaxin in April 2021. The results from the study will help stakeholders to efficiently use social media to disseminate COVID-19 vaccine information on popular concerns. This in turn will encourage citizens to be vaccinated and achieve herd immunity. Similar methodology can be adopted in future to understand the perceptions and concerns of people in emergency situations. Supplementary Information: The online version contains supplementary material available at 10.1007/s42001-023-00203-0.
ABSTRACT
Burden due to infectious and noncommunicable disease is increasing at an alarming rate. Social media usage is growing rapidly and has become the new norm of communication. It is imperative to examine what is being discussed in the social media about diseases or conditions and the characteristics of the network of people involved in discussion. The objective is to assess the tools and techniques used to study social media disease networks using network analysis and network modeling. PubMed and IEEEXplore were searched from 2009 to 2020 and included 30 studies after screening and analysis. Twitter, QuitNet, and disease-specific online forums were widely used to study communications on various health conditions. Most of the studies have performed content analysis and network analysis, whereas network modeling has been done in six studies. Posts on cancer, COVID-19, and smoking have been widely studied. Tools and techniques used for network analysis are listed. Health-related social media data can be leveraged for network analysis. Network modeling technique would help to identify the structural factors associated with the affiliation of the disease networks, which is scarcely utilized. This will help public health professionals to tailor targeted interventions.
Subject(s)
COVID-19 , Social Media , Humans , Public Health , SARS-CoV-2 , Social Network AnalysisABSTRACT
BACKGROUND: The recent outbreak of respiratory illness caused by COVID-19 in Wuhan, China, has received global attention as it has infected thousands of individuals there, and later it has also been reported from other countries internationally. This study aims at performing an exploratory study on Twitter to understand the information shared among the community regarding the COVID-19 outbreak. METHODS: COVID-19 related tweets were collected from Twitter using keywords from 18 January to 25 January 2020. Top-ranking tweets were taken as samples and then categorised based on the content. Expressions or opinion tweets were analysed qualitatively to understand the mindset of the people regarding the outbreak. Theme wise reachability evaluation of the messages was also performed. RESULTS: Based on the content of the tweets, five themes were evolved: (1) general information; (2) health information; (3) expressions; (4) humour and (5) others. 57.42% of messages are general information followed by expressive tweets (24.12%). Humorous messages were liked the most, whereas health information tweets were retweeted the maximum. Fear was the predominant emotion expressed in the messages. CONCLUSION: The results of the study would be useful to focus on the dissemination of the right information and effective communication on Twitter related to health and outbreak management.