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Exploring the influence of user characteristics on verbal aggression towards social chatbots.

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Title: Exploring the influence of user characteristics on verbal aggression towards social chatbots.
Authors: Chin, HyoJin, Yong Yi, Mun
Source: Behaviour & Information Technology. May2025, Vol. 44 Issue 8, p1576-1594. 19p.
Subjects: Language & languages, Research funding, Cronbach's alpha, Sex distribution, Interviewing, Emotions, Descriptive statistics, Mann Whitney U Test, Aggression (Psychology), Experimental design, Ethics, Guilt (Psychology), Research, Research methodology, Social skills, Shame, Interpersonal relations, Sociodemographic factors, Comparative studies, Verbal behavior, Chatbots, User interfaces
Abstract: Chatbots possess great potential benefits, yet concerns persist regarding users adopting inappropriate, offensive language. This research delved into the influence of user characteristics on verbally aggressive behaviours towards social chatbots. Employing a mixed-method study, we examined individual characteristics such as personal dispositions, offensive language patterns, academic majors, and prior experiences with conversational agents. Findings from a ten-day field experiment involving 33 participants using a real-world Telegram-based chatbot app unveiled that users' anthropomorphism, computer-related major, and gender significantly impact their moral emotions and evaluations of the chatbot's capabilities. Moreover, employing offensive language towards the chatbot detrimentally impacted users' perceptions of its abilities, helpfulness, and likability. The research findings advocate for ongoing monitoring and effective resolution of users' behaviours regarding the use of offensive language in their interactions with a chatbot. Additionally, the results underscore the importance of incorporating diverse perspectives into chatbot design to address biases and offensive utterances. [ABSTRACT FROM AUTHOR]
Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Exploring the influence of user characteristics on verbal aggression towards social chatbots.
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  Data: <searchLink fieldCode="AR" term="%22Chin%2C+HyoJin%22">Chin, HyoJin</searchLink><br /><searchLink fieldCode="AR" term="%22Yong+Yi%2C+Mun%22">Yong Yi, Mun</searchLink>
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  Data: Chatbots possess great potential benefits, yet concerns persist regarding users adopting inappropriate, offensive language. This research delved into the influence of user characteristics on verbally aggressive behaviours towards social chatbots. Employing a mixed-method study, we examined individual characteristics such as personal dispositions, offensive language patterns, academic majors, and prior experiences with conversational agents. Findings from a ten-day field experiment involving 33 participants using a real-world Telegram-based chatbot app unveiled that users' anthropomorphism, computer-related major, and gender significantly impact their moral emotions and evaluations of the chatbot's capabilities. Moreover, employing offensive language towards the chatbot detrimentally impacted users' perceptions of its abilities, helpfulness, and likability. The research findings advocate for ongoing monitoring and effective resolution of users' behaviours regarding the use of offensive language in their interactions with a chatbot. Additionally, the results underscore the importance of incorporating diverse perspectives into chatbot design to address biases and offensive utterances. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1080/0144929X.2024.2362957
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      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 1576
    Subjects:
      – SubjectFull: Language & languages
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Cronbach's alpha
        Type: general
      – SubjectFull: Sex distribution
        Type: general
      – SubjectFull: Interviewing
        Type: general
      – SubjectFull: Emotions
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Mann Whitney U Test
        Type: general
      – SubjectFull: Aggression (Psychology)
        Type: general
      – SubjectFull: Experimental design
        Type: general
      – SubjectFull: Ethics
        Type: general
      – SubjectFull: Guilt (Psychology)
        Type: general
      – SubjectFull: Research
        Type: general
      – SubjectFull: Research methodology
        Type: general
      – SubjectFull: Social skills
        Type: general
      – SubjectFull: Shame
        Type: general
      – SubjectFull: Interpersonal relations
        Type: general
      – SubjectFull: Sociodemographic factors
        Type: general
      – SubjectFull: Comparative studies
        Type: general
      – SubjectFull: Verbal behavior
        Type: general
      – SubjectFull: Chatbots
        Type: general
      – SubjectFull: User interfaces
        Type: general
    Titles:
      – TitleFull: Exploring the influence of user characteristics on verbal aggression towards social chatbots.
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            – D: 15
              M: 05
              Text: May2025
              Type: published
              Y: 2025
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