Contact Tracing Of Covid-19 Patients Using Tweets

Abstract

Covid-19 has had an impact on everyone’s lives in the recent past. Presently the field of healthcare uses social media as a tool for professional education and communication. The benefits and drawbacks of these networks have been widely discussed in different research papers. Due to the Covid-19 pandemic, the biggest problem that the government is facing is identifying the close contacts of the Covid-19 patients. Most of the people avoid revealing the truth about the places they visit and people they met in the recent past to the Covid-19 controlling bodies. But people use social media in their day to day life to post/ share their life experiences. Some people use twitter to share their experiences related to Covid-19. In this research paper we focus on tracing the Covid-19 close contacts using tweets. The proposed approach creates a dataset using a twitter API and filters the covid-19 positive users using sentimental analysis. After filtered positive users from the dataset, we have used a set of keywords to filter individual users’ tweets and then we have applied name entity recognition to identify the connected people and places. After gathering each tweet user’s information, we have visualized the relevant relationships of each close contact in a network diagram. Our proposed model indicates 75% accuracy by tracing down Covid-19 positive users and close contacts.