Posted: September 28th, 2022

Social Media for Flu Prediction

Social Media for Flu Prediction
The recent revelation on how IBM utilized big data to predict flu outbreaks via social media is a clear indicator of the big strides happening in technology. IBM Infosphere BigInsights platform was used to conduct digital surveillance on Twitter with the goal of detecting, tracking, and mapping flu-related content posted on Twitter (Zadeh, 2015). The project was successful in providing a close correlation between clinic flu encounters and online posts. This can be attributed to social media’s exponential growth since the introduction of smartphones and the belief that the internet has all the answers. Currently, most families in the U.S. have a smartphone or computer which they use to access social media. Most individuals also trust social media applications such as Twitter where they converse with close friends and acquaintances. Therefore, information such as flu signs and symptoms are openly shared and discussed.
Apart from using Twitter and social media applications, Google Search Trends is another viable option. Google has a wide array of applications that store vital user information, such as texts, locations, user profiles, and photos. Therefore using Google is a worthy route since data is easily accessible without the need for APIs and other forms of integrations. More so, Google is a well-established company with top-notch resources. Other variables include traditional weather and climate factors and deep learning which uses multiples layers of data to extract higher level features from raw input progressively. Furthermore, the advancements witnessed in big data enable effective digital surveillance operations. Given that nowadays, people prefer to use social media and the internet to diagnose their illnesses and infections, it is much easier to track illnesses online. Self-diagnosis has led to a decrease in hospital walk-ins to the extent doctors are now venturing into online-based solutions.
References
Zadeh, A. H., Zolbanin, H. M., Sharda, R., & Delen, D. (2015). Social media for nowcasting the flu activity: Spatial-temporal and text analysis. Business Analytics Congress, Pre-ICIS Conference, Fort Worth, TX.

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