Chloe for COVID-19: Evolution of an Intelligent Conversational Agent to Address Infodemic Management Needs During the COVID-19 Pandemic

Siedlikowski, Sophia; Noël, Louis-Philippe; Moynihan, Stephanie Anne; Robin, Marc R.

doi:10.2196/27283

Cited by 20 publications

(36 citation statements)

References 23 publications

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“…Chatbots have several advantages over human interaction partners or other online services. For example, chatbots operate at a low cost and are available around the clock to handle user queries [ 4 , 8 , 9 ]. Furthermore, they can provide more concise and less overwhelming information than the lengthy list of results offered by social media or search engines [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…In comparison, studies on chatbots are scarce. Studies on COVID-19 have been limited to literature reviews on existing chatbots and how they could be changed for the pandemic [ 9 , 18 , 19 ] and a study on how to use artificial intelligence (AI) techniques to make a COVID-19 chatbot [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, some chatbot users perceive that bots can be helpful when they cannot receive social support from others [ 30 ]. Chatbots are also cost-efficient; they can simultaneously communicate with millions of people in different local languages while educating the public about COVID-19 [ 8 , 9 ]. Moreover, chatbots generate more succinct responses than social media or search engines and can promptly respond to user questions around the clock [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…In the health domain, the literature has focused on the role of chatbots in promoting mental health [ 34 , 35 ], responding to telemedicine needs [ 36 , 37 ], or answering questions about COVID-19 [ 38 , 39 ]. Some studies have proposed design frameworks for developing chatbots that provide information related to COVID-19 [ 8 , 40 ]. However, no study has looked into how people interact with live chatbots in the real world, which is the subject of this paper.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

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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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

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“…The interface of a chatbot that is familiar to most people with experiences in mobile messaging could promote the usability and user engagement of the chatbot compared to other platforms. Several chatbots have been developed amid the COVID-19 pandemic [ 11 , 12 ], mostly for symptom checking and information dissemination [ 13 , 14 ]. The WHO has also launched chatbots on popular social networking sites such as WhatsApp to provide instant and credible information about COVID-19, including vaccination [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Efficacy, Usability, and Acceptability of a Chatbot for Promoting COVID-19 Vaccination in Unvaccinated or Booster-Hesitant Young Adults: Pre-Post Pilot Study

Luk¹,

Lui²,

Wang³

2022

J Med Internet Res

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Background COVID-19 vaccines are highly effective in preventing severe disease and death but are underused. Interventions to address COVID-19 vaccine hesitancy are paramount to reducing the burden of COVID-19. Objective We aimed to evaluate the preliminary efficacy, usability, and acceptability of a chatbot for promoting COVID-19 vaccination and examine the factors associated with COVID-19 vaccine hesitancy. Methods In November 2021, we conducted a pre-post pilot study to evaluate “Vac Chat, Fact Check,” a web-based chatbot for promoting COVID-19 vaccination. We conducted a web-based survey (N=290) on COVID-19 vaccination at a university in Hong Kong. A subset of 46 participants who were either unvaccinated (n=22) or were vaccinated but hesitant to receive boosters (n=24) were selected and given access to the chatbot for a 7-day trial period. The chatbot provided information about COVID-19 vaccination (eg, efficacy and common side effects), debunked common myths about the vaccine, and included a decision aid for selecting vaccine platforms (inactivated and mRNA vaccines). The main efficacy outcome was changes in the COVID-19 Vaccine Hesitancy Scale (VHS) score (range 9-45) from preintervention (web-based survey) to postintervention (immediately posttrial). Other efficacy outcomes included changes in intention to vaccinate or receive boosters and willingness to encourage others to vaccinate on a scale from 1 (not at all) to 5 (very). Usability was assessed by the System Usability Scale (range 0-100). Linear regression was used to examine the factors associated with COVID-19 VHS scores in all survey respondents. Results The mean (SD) age of all survey respondents was 21.4 (6.3) years, and 61% (177/290) of respondents were female. Higher eHealth literacy (B=–0.26; P<.001) and perceived danger of COVID-19 (B=–0.17; P=.009) were associated with lower COVID-19 vaccine hesitancy, adjusting for age, sex, chronic disease status, previous flu vaccination, and perceived susceptibility to COVID-19. The main efficacy outcome of COVID-19 VHS score significantly decreased from 28.6 (preintervention) to 24.5 (postintervention), with a mean difference of –4.2 (P<.001) and an effect size (Cohen d) of 0.94. The intention to vaccinate increased from 3.0 to 3.9 (P<.001) in unvaccinated participants, whereas the intention to receive boosters increased from 1.9 to 2.8 (P<.001) in booster-hesitant participants. Willingness to encourage others to vaccinate increased from 2.7 to 3.0 (P=.04). At postintervention, the median (IQR) System Usability Scale score was 72.5 (65-77.5), whereas the median (IQR) recommendation score was 7 (6-8) on a scale from 0 to 10. In a post hoc 4-month follow-up, 82% (18/22) of initially unvaccinated participants reported having received the COVID-19 vaccine, whereas 29% (7/24) of booster-hesitant participants received boosters. Conclusions This pilot study provided initial evidence to support the efficacy, usability, and acceptability of a chatbot for promoting COVID-19 vaccination in young adults who were unvaccinated or booster-hesitant.

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Comparing button-based chatbots with webpages for presenting fact-checking results: A case study of health information

Zhao

Chen

Jin

et al. 2023

Information Processing & Management

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Chloe for COVID-19: Evolution of an Intelligent Conversational Agent to Address Infodemic Management Needs During the COVID-19 Pandemic

Cited by 20 publications

References 23 publications

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

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

Efficacy, Usability, and Acceptability of a Chatbot for Promoting COVID-19 Vaccination in Unvaccinated or Booster-Hesitant Young Adults: Pre-Post Pilot Study

Comparing button-based chatbots with webpages for presenting fact-checking results: A case study of health information

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