New study shows how people interacted with chatbots during COVID-19 pandemic
The COVID-19 pandemic has increased people's reliance on digital platforms, such as social media, to obtain information and communicate their thoughts and emotions with their peers. The sudden shift from offline to online ...
A new study has shown the potential of AI chatbots to relieve users' anxiety and quickly deliver information during major social upheavals. Led by Chief Investigator Cha Meeyoung of the Data Science Group within the Institute for Basic Science (IBS) and Dr. Cha Chiyoung from Ewha Woman's University's College of Nursing, the researchers analyzed nearly 20,000 conversations between online users and a chatbot called SimSimi.
This commercial chatbot has served over 400 million users worldwide in 81 languages. The joint research team investigated how users from the United States, United Kingdom, Canada, Malaysia, and the Philippines used the chatbot during the COVID-19 pandemic.
This study is one of the first to analyze large-scale data on conversations related to COVID-19 between chatbots and humans.
Dr. Chin Hyojin, the lead author of the study said, "Chatbots are a promising tool to fulfill people's informational needs in challenging times. While health institutions such as the Korea Center for Disease Control and Prevention and the World Health Organization (WHO) have used chatbots to provide the most up-to-date information on the spread and symptoms of COVID-19 to billions of people, it was unclear how users interacted with such systems in times of crisis."
During the Covid-19 pandemic, users sought health-related information and shared emotional messages with the chatbot, indicating the potential use of chatbots to provide accurate health information and emotional support. Credit: Institute for Basic Science
The average percentage of positive and negative-related words in COVID-19–related conversations by country according to the Linguistic Inquiry and Word Count dictionary. Credit: Institute for Basic Science
Topics discussed by users with the chatbot identified by the Latent Dirichlet Allocation topic model and their prevalence. Credit: Institute for Basic Science