Vaccine Sentiments

Vaccine hesitancy is a continuum ranging from full vaccine acceptance to full vaccine rejection, with some acceptance, delay, and refusal in between. Vaccine-preventable diseases have been shown to kill more than 3 million people on average per year and have been named one of the top ten global health threats deemed by the World Health Organization (WHO) since 2019. Despite the overwhelming evidence of its benefits, there is still a growing public vaccine hesitancy globally. Individuals and groups continue to challenge the effectiveness of vaccinations. Information-oriented social media, such as Twitter, are at the forefront of the vaccine challenge as it is one of the first lines of a news source for the general public.

Twitter and other social media platforms have been viewed as an effective tool for health research and are rich with metadata. However, the process of extracting data from online sources, cleaning and transforming data, and creating interactive dashboards is a laborious task. Oftentimes, the whole process involves the use of multiple tools and detailed knowledge of computer programming (aka coding). For those interested in such data-driven understanding of such important topics, this can take days to weeks to be an impossible task to perform. Creating insightful reports and views to study important topics such as vaccine hesitancy is crucial to health science. Yet, researchers are limited by the tools and additional knowledge required for data extraction to visualization. Indeed, any such researcher can work with spreadsheets (like) interfaces. Therefore, a natural solution for this important challenge is enabling individuals to performance data analysis with the ease of spreadsheets.

With its Generative AI platform for tabular and time series data, Ikigai enables health researchers to easily connect to online data sources using aiMatch. There is no need for writing code when trying to connect to online sources, such as social media data. Once you connect to your data source (e.g. Twitter API), cleaning and transforming your data (i.e. such as processing the tweet text, converting location data, and joining state/county-level data) is a breeze with the drag and drop features of the platform. The end result can include dashboards that can interact with your every filter and search. The dashboards are fully customizable and limited only to your imagination!

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Interested in building your own data-driven dashboard, get access to Ikigai.

About the Author

Aldreen Venzon (Data Success Manager)

Aldreen is a Registered Nurse with experience in data science and analytics from a global Fortune 500 technology company to nationally-renowned healthcare systems. He is also currently a Ph.D. candidate in Nursing Leadership & Computational Social Science at University of California Davis.

Originally published on medium.com