FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313451641> ?p ?o ?g. }

• W4313451641 endingPage "e40922" @default.
• W4313451641 startingPage "e40922" @default.
• W4313451641 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." @default.
• W4313451641 created "2023-01-06" @default.
• W4313451641 creator A5007390351 @default.
• W4313451641 creator A5007983942 @default.
• W4313451641 creator A5011245772 @default.
• W4313451641 creator A5043560474 @default.
• W4313451641 creator A5061810530 @default.
• W4313451641 creator A5081179169 @default.
• W4313451641 creator A5089207342 @default.
• W4313451641 date "2023-01-27" @default.
• W4313451641 modified "2023-10-05" @default.
• W4313451641 title "User-Chatbot Conversations During the COVID-19 Pandemic: Study Based on Topic Modeling and Sentiment Analysis" @default.
• W4313451641 cites W2001829221 @default.
• W4313451641 cites W2065757342 @default.
• W4313451641 cites W2076253284 @default.
• W4313451641 cites W2099386544 @default.
• W4313451641 cites W2461136067 @default.
• W4313451641 cites W2471350540 @default.
• W4313451641 cites W2581789519 @default.
• W4313451641 cites W2623779865 @default.
• W4313451641 cites W2889335577 @default.
• W4313451641 cites W2964309167 @default.
• W4313451641 cites W3009936362 @default.
• W4313451641 cites W3012290708 @default.
• W4313451641 cites W3015218641 @default.
• W4313451641 cites W3017885019 @default.
• W4313451641 cites W3021999948 @default.
• W4313451641 cites W3023498144 @default.
• W4313451641 cites W3030172318 @default.
• W4313451641 cites W3041990891 @default.
• W4313451641 cites W3084408270 @default.
• W4313451641 cites W3088268279 @default.
• W4313451641 cites W3092152105 @default.
• W4313451641 cites W3094221957 @default.
• W4313451641 cites W3096451393 @default.
• W4313451641 cites W3101739755 @default.
• W4313451641 cites W3115922900 @default.
• W4313451641 cites W3121269699 @default.
• W4313451641 cites W3124516888 @default.
• W4313451641 cites W3128585438 @default.
• W4313451641 cites W3130961600 @default.
• W4313451641 cites W3133702157 @default.
• W4313451641 cites W3134175649 @default.
• W4313451641 cites W3138942390 @default.
• W4313451641 cites W3146304353 @default.
• W4313451641 cites W3162547504 @default.
• W4313451641 cites W3171010408 @default.
• W4313451641 cites W3171261489 @default.
• W4313451641 cites W3185727834 @default.
• W4313451641 cites W3186542042 @default.
• W4313451641 cites W3193227769 @default.
• W4313451641 cites W3193311321 @default.
• W4313451641 cites W3210814791 @default.
• W4313451641 cites W4200028970 @default.
• W4313451641 cites W4206536415 @default.
• W4313451641 cites W4210523443 @default.
• W4313451641 cites W4212906647 @default.
• W4313451641 cites W4224312622 @default.
• W4313451641 cites W651054463 @default.
• W4313451641 doi "https://doi.org/10.2196/40922" @default.
• W4313451641 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36596214" @default.
• W4313451641 hasPublicationYear "2023" @default.
• W4313451641 type Work @default.
• W4313451641 citedByCount "8" @default.
• W4313451641 countsByYear W43134516412023 @default.
• W4313451641 crossrefType "journal-article" @default.
• W4313451641 hasAuthorship W4313451641A5007390351 @default.
• W4313451641 hasAuthorship W4313451641A5007983942 @default.
• W4313451641 hasAuthorship W4313451641A5011245772 @default.
• W4313451641 hasAuthorship W4313451641A5043560474 @default.
• W4313451641 hasAuthorship W4313451641A5061810530 @default.
• W4313451641 hasAuthorship W4313451641A5081179169 @default.
• W4313451641 hasAuthorship W4313451641A5089207342 @default.
• W4313451641 hasBestOaLocation W43134516411 @default.
• W4313451641 hasConcept C108827166 @default.
• W4313451641 hasConcept C136764020 @default.
• W4313451641 hasConcept C138816342 @default.
• W4313451641 hasConcept C142724271 @default.
• W4313451641 hasConcept C154945302 @default.
• W4313451641 hasConcept C15744967 @default.
• W4313451641 hasConcept C159110408 @default.
• W4313451641 hasConcept C2777200299 @default.
• W4313451641 hasConcept C2779041454 @default.
• W4313451641 hasConcept C2779134260 @default.
• W4313451641 hasConcept C3008058167 @default.
• W4313451641 hasConcept C41008148 @default.
• W4313451641 hasConcept C46312422 @default.
• W4313451641 hasConcept C518677369 @default.
• W4313451641 hasConcept C524204448 @default.
• W4313451641 hasConcept C66402592 @default.
• W4313451641 hasConcept C71924100 @default.
• W4313451641 hasConcept C89623803 @default.
• W4313451641 hasConceptScore W4313451641C108827166 @default.
• W4313451641 hasConceptScore W4313451641C136764020 @default.
• W4313451641 hasConceptScore W4313451641C138816342 @default.
• W4313451641 hasConceptScore W4313451641C142724271 @default.
• W4313451641 hasConceptScore W4313451641C154945302 @default.
• W4313451641 hasConceptScore W4313451641C15744967 @default.

• next