Title:Twitter Trends Reveals: Focus of Interest in the Sleep Trend Analytics on Response to COVID-19 Outbreak
Volume: 17
Issue: 1
Author(s): Surbhi Bhatia*Anubhav Tyagi
Affiliation:
- Department of Information Systems, College of Computer Sciences and Information Technology, King Faisal University, Hofuf,Saudi Arabia
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.
