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Personalized Interaction-Focused Interventions for Mitigating Misinformation.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Personalized Interaction-Focused Interventions for Mitigating Misinformation./
作者:
Siddiqui, Safat.
面頁冊數:
1 online resource (122 pages)
附註:
Source: Dissertations Abstracts International, Volume: 84-04, Section: B.
Contained By:
Dissertations Abstracts International84-04B.
標題:
Computer science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29327708click for full text (PQDT)
ISBN:
9798845423108
Personalized Interaction-Focused Interventions for Mitigating Misinformation.
Siddiqui, Safat.
Personalized Interaction-Focused Interventions for Mitigating Misinformation.
- 1 online resource (122 pages)
Source: Dissertations Abstracts International, Volume: 84-04, Section: B.
Thesis (Ph.D.)--The University of North Carolina at Charlotte, 2022.
Includes bibliographical references
This dissertation addresses a novel approach to assessing users' interaction tendencies on social media as a basis for personalized interventions that can make the truth louder and mitigate the spread of misinformation. This research leverages users' high and low interaction tendencies to amplify truth by increasing users' interactions with verified posts and decreasing their interactions with unverified posts. For designing personalized interaction-focused interventions, this dissertation presents an Active-Passive (AP) framework and three principles of social media interactions to make the truth louder on social media. This dissertation presents a study including tasks and questionnaires to investigate users' differences in the Active-Passive (AP) framework for utilizing platforms' basic interaction functionalities, such as like, comment, or share buttons. The results show that users use the interaction functionalities differently due to their interaction tendencies; users with high interaction tendencies use more interaction functionalities, and users with low interaction tendencies use less. This dissertation presents an analysis of participants' responses to the design principles and investigates users' additional sharing functionality usage and preference for platform-based incentives. The results show that users with lower interaction tendencies share verified information more when they receive additional interaction support. Furthermore, due to the interaction tendencies, users exhibit opposite preferences for platform-based incentives that can encourage their participation in making the truth louder. Users with high interaction tendencies prefer incentives that highlight their presence on the platform, and users with low interaction tendencies favor incentives that can educate them about the impact of their participation on their friends and community. This dissertation concludes with a discussion on personalized interaction-focused interventions and provides directions for future research.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023
Mode of access: World Wide Web
ISBN: 9798845423108Subjects--Topical Terms:
523869
Computer science.
Subjects--Index Terms:
Fact checkingIndex Terms--Genre/Form:
542853
Electronic books.
Personalized Interaction-Focused Interventions for Mitigating Misinformation.
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Source: Dissertations Abstracts International, Volume: 84-04, Section: B.
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This dissertation addresses a novel approach to assessing users' interaction tendencies on social media as a basis for personalized interventions that can make the truth louder and mitigate the spread of misinformation. This research leverages users' high and low interaction tendencies to amplify truth by increasing users' interactions with verified posts and decreasing their interactions with unverified posts. For designing personalized interaction-focused interventions, this dissertation presents an Active-Passive (AP) framework and three principles of social media interactions to make the truth louder on social media. This dissertation presents a study including tasks and questionnaires to investigate users' differences in the Active-Passive (AP) framework for utilizing platforms' basic interaction functionalities, such as like, comment, or share buttons. The results show that users use the interaction functionalities differently due to their interaction tendencies; users with high interaction tendencies use more interaction functionalities, and users with low interaction tendencies use less. This dissertation presents an analysis of participants' responses to the design principles and investigates users' additional sharing functionality usage and preference for platform-based incentives. The results show that users with lower interaction tendencies share verified information more when they receive additional interaction support. Furthermore, due to the interaction tendencies, users exhibit opposite preferences for platform-based incentives that can encourage their participation in making the truth louder. Users with high interaction tendencies prefer incentives that highlight their presence on the platform, and users with low interaction tendencies favor incentives that can educate them about the impact of their participation on their friends and community. This dissertation concludes with a discussion on personalized interaction-focused interventions and provides directions for future research.
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