Abstract
Background: The unprecedented pressures have arrived from pandemic on each country to make compelling requisites for controlling the population by assessing the cases and properly utilizing available resources. The rapid number of exponential cases globally have become the apprehension of panic, fear and anxiety among people. Currently, more than two million people tested positive. Therefore, it’s the need of the situation to implement different measures like lockdown and social distancing to prevent the country by demystifying the pertinent facts and information.
Methods: The goal of this work is to extract the tweets having different users and different geographic locations, preprocess it by applying the filtration tasks and then data engineering methods to identify how the mental and physical health is directly proportional to this pandemic disease; because of the rapid spread of the false information on social media.
Results: This work focuses on observing the increase in frequency of tweets and the last logout timings on twitter during lock down of different users in India by using data analytics. The study claims that it has having adverse effects and is directly affecting the sleep pattern which may prove to be the root causes of several diseases such as depression in future.
Conclusion: It has been observed that prevalence of lockdown has actually led to disorder in the sleep pattern of individuals. The study validates through experiments and have shown analysis that people tend to tweet more in night-time past (twelve am) which shows the growing trend of sleep disorders.
Graphical Abstract
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