The world is facing the worst pandemic in a century because of Covid-19. Spanish flu during 1920 was the last such deadly influenza pandemic after which the current world has seen tremendous technological advancements. Internet and social media is one such advancement that connects billions of people. It has become very easy to express people’s thoughts through tweets and posts that reach a lot of people in a short period.
Recent statistics show that there is up to a 45% increase in the usage of social media. People not just share news about Covid-19 topics but also express their sentiments on it. For example, people show fear, anger, racism, etc., With the advancements of IoT, each tweet or post is associated with time and location information. Thus more insights can be gained by understanding the topics with spatio-temporal dynamics.
Machine learning, especially text mining techniques like topic modeling and sentiment analysis would help to understand what people talk about Covid-19 and how the sentiments shift during this pandemic. This can bring enormous insights for government organizations based on which any necessary actions can be made.
This talk will focus on the applications of different machine learning techniques to understand people dynamics in social media during the Covid-19 pandemic.
Thirunavukarasu Balasubramaniam will be speaking at International Congress on International Congress on Social Computing and Networking 2021 which is scheduled to happen on 13th and 14th August 2021 at Hong Kong, HKSAR.