Novel Approach on sustainable Topic Modelling paradigms for Recognition of health-related topics in a social platform through Distributed file system

Abstract

social media is one of the most sustainable and prominent features of the Internet and has a vast amount of influence in today’s world. All the latest information regarding every topic is available on social media i.e., social media serves as a sustainable repository of the latest information, particularly Twitter where discourse on every major trending topic takes place and is shown to the user hence it is utilized by many individuals all over the world to keep themselves updated with the latest news occurring everywhere in the world. In Current time due to the pandemic, Twitter also played a key role in relaying updated and accurate information regarding many topics related to health care. Millions of people everyday share their ideas and opinions regarding health-related concepts. To analyze these many tweets which contain billions of users is a challenging task and so to understand the key features or topics discussed by the user’s artificial intelligence has a branch called Natural language processing also called as NLP which can help in analyzing texts from a huge amount of dataset. Topic modeling, which is a part of NLP helps in analyzing healthcare data extracted from twitter which would provide a description of current trending healthcare topics and development of most significant tweets and their content.