{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/115956"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/115956","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Using chatbots to correct COVID-19 misinformation: a controlled experiment","abstract":"This Thesis was approved for publication on 2022-07-22 at 09:44.","abstract_html":"This Thesis was approved for publication on 2022-07-22 at 09:44.","abstract_has_math":false,"creators":["Gong, Ziyang"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Advertising","degree_department":null,"school":null,"contributors":["Su, Leona Yi-Fan","Wise, Kevin","Sar, Sela"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-08","date_published":"2022-08","updated_at":"2026-07-22T22:24:55Z","subjects":["chatbot","conversational agent","empathy","interactivity","misperception","vaccination intention","COVID-19"],"languages":["en","eng"],"rights":["Copyright 2022 Ziyang Gong"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/115956","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Su, Leona Yi-Fan","Wise, Kevin","Sar, Sela"]},{"key":"dc:creator","label":"Author","values":["Gong, Ziyang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-08","2022-07-22"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Advertising"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["chatbot","conversational agent","empathy","interactivity","misperception","vaccination intention","COVID-19"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2022 Ziyang Gong"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/115956"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This Thesis was approved for publication on 2022-07-22 at 09:44.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18395 on 2022-11-16 at 10:56:39","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-08-01","The student, Ziyang Gong, accepted the attached license on 2022-07-20 at 23:23.","The student, Ziyang Gong, submitted this Thesis for approval on 2022-07-20 at 23:47.","Conversational agents, otherwise known as chatbots, have been increasingly used by organizations worldwide to provide health-related information and correct misinformation in the COVID-19 pandemic. However, previous studies have neither empirically investigated the effectiveness of correcting misinformation using chatbots, nor have they provided theory-based guidelines for the designing of such chatbots. To address these concerns, we developed our misinformation-correcting chatbots and conducted two experiments. In the pre-test experiment (n = 42), we examined whether corrective information provided through chatbot interactions can correct COVID-related misperception and behavioral intention compared to not receiving such information. In the official study (n = 791), we investigate whether and how chatbots with interactive conversational cues and/or empathetic conversational cues can outperform the basic chatbot in correcting users’ COVID-19-vaccination misperception and enhancing users’ vaccination intention. Our results indicate that chatbots can be effective in fighting against misinformation and interactive and empathetic conversational cues do affect users’ psychological perception towards the chatbot and in turn leads to better interaction outcomes. We also identified different mechanisms of people’s misperception change and behavioral intention change. Theoretical and practical implications are discussed."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Using chatbots to correct COVID-19 misinformation: a controlled experiment"]}]}],"canonical_facts":{"dc:contributor":["Su, Leona Yi-Fan","Wise, Kevin","Sar, Sela"],"dc:creator":["Gong, Ziyang"],"dc:date":["2022-08","2022-07-22"],"dc:description":["This Thesis was approved for publication on 2022-07-22 at 09:44.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18395 on 2022-11-16 at 10:56:39","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-08-01","The student, Ziyang Gong, accepted the attached license on 2022-07-20 at 23:23.","The student, Ziyang Gong, submitted this Thesis for approval on 2022-07-20 at 23:47.","Conversational agents, otherwise known as chatbots, have been increasingly used by organizations worldwide to provide health-related information and correct misinformation in the COVID-19 pandemic. However, previous studies have neither empirically investigated the effectiveness of correcting misinformation using chatbots, nor have they provided theory-based guidelines for the designing of such chatbots. To address these concerns, we developed our misinformation-correcting chatbots and conducted two experiments. In the pre-test experiment (n = 42), we examined whether corrective information provided through chatbot interactions can correct COVID-related misperception and behavioral intention compared to not receiving such information. In the official study (n = 791), we investigate whether and how chatbots with interactive conversational cues and/or empathetic conversational cues can outperform the basic chatbot in correcting users’ COVID-19-vaccination misperception and enhancing users’ vaccination intention. Our results indicate that chatbots can be effective in fighting against misinformation and interactive and empathetic conversational cues do affect users’ psychological perception towards the chatbot and in turn leads to better interaction outcomes. We also identified different mechanisms of people’s misperception change and behavioral intention change. Theoretical and practical implications are discussed."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/115956"],"dc:language":["en","eng"],"dc:rights":["Copyright 2022 Ziyang Gong"],"dc:subject":["chatbot","conversational agent","empathy","interactivity","misperception","vaccination intention","COVID-19"],"dc:title":["Using chatbots to correct COVID-19 misinformation: a controlled experiment"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Advertising"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:55Z"}