User-Chatbot Conversations During the COVID-19 Pandemic: Study Based on Topic Modeling and Sentiment Analysis

Abstract

Background Chatbots have become a promising tool to support public health initiatives. Despite their potential, little research has examined how individuals interacted with chatbots during the COVID-19 pandemic. Understanding user-chatbot interactions is crucial for developing services that can respond to people’s needs during a global health emergency. Objective This study examined the COVID-19 pandemic–related topics online users discussed with a commercially available social chatbot and compared the sentiment expressed by users from 5 culturally different countries. Methods We analyzed 19,782 conversation utterances related to COVID-19 covering 5 countries (the United States, the United Kingdom, Canada, Malaysia, and the Philippines) between 2020 and 2021, from SimSimi, one of the world’s largest open-domain social chatbots. We identified chat topics using natural language processing methods and analyzed their emotional sentiments. Additionally, we compared the topic and sentiment variations in the COVID-19–related chats across countries. Results Our analysis identified 18 emerging topics, which could be categorized into the following 5 overarching themes: “Questions on COVID-19 asked to the chatbot” (30.6%), “Preventive behaviors” (25.3%), “Outbreak of COVID-19” (16.4%), “Physical and psychological impact of COVID-19” (16.0%), and “People and life in the pandemic” (11.7%). Our data indicated that people considered chatbots as a source of information about the pandemic, for example, by asking health-related questions. Users turned to SimSimi for conversation and emotional messages when offline social interactions became limited during the lockdown period. Users were more likely to express negative sentiments when conversing about topics related to masks, lockdowns, case counts, and their worries about the pandemic. In contrast, small talk with the chatbot was largely accompanied by positive sentiment. We also found cultural differences, with negative words being used more often by users in the United States than by those in Asia when talking about COVID-19. Conclusions Based on the analysis of user-chatbot interactions on a live platform, this work provides insights into people’s informational and emotional needs during a global health crisis. 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. Future research can look into different support strategies that align with the direction of public health policy.

The Chatbots Are Invading Us: A Map Point on the Evolution, Applications, Opportunities, and Emerging Problems in the Health Domain

“…The chatbots are increasingly showing several applications in the health domain . Diverse keywords [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 ] are associated with the concept of the chatbot in healthcare; among the most frequent we find: patient engagement, clinical support, mental health, health monitoring, patient education, appointment scheduling, symptom checking, chronic disease management, triage, remote monitoring, telemedicine, health coaching and emergency response.…”

“…Chatbots can be used in several fields in the health domain [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 ]: (a) As a tool for answering frequently asked questions [ 39 ]; (b) For the collection of data and patient details [ 39 , 42 , 43 ]; (c) To support patients finding a doctor or a specific service, on managing appointments, and on the medication dispensing procedure [ 42 ]; (d) As an interactive guide to the management of self-assessment and symptom control [ 39 , 42 ]; (e) As a tool to guide an interactive triage, applicable in the case of an emergency as well [ 36 ]; (f) In telehealth, digital health applications, and remote monitoring [ 37 , 39 , 40 , 42 , 43 ]. (g) In the learning process, in the construction of scientific knowledge and in supporting scientific dissemination [ 35 , 38 ]; (h) In mental health applications [ 37 , 38 ]; (i) For physical wellness and health coaching [ 40 ].…”

Impact of ChatGPT on medical chatbots as a disruptive technology

“…We must admit that the chatbot is extremely popular, as it is very user-friendly, and patients as users may focus more on the benefits of convenience and efficiency, rather than the reliability and accuracy of the tool (Chin et al, 2023 ). ChatGPT also presents an air of authority and so sounds rather trustworthy.…”

Machine Learning Chatbot for Sentiment Analysis of Covid-19 Tweets

“…Chin et al [15] analyzed 19,782 conversation utterances that are related to COVID-19 which cover different countries between 2020 and 2021. The authors identified chat topics (NLP) methods to analyze the emotional sentiments.…”