[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-85514-en":3,"doc-seo-85514-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},85514,34359740700684,"Finn","https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487",8,"Research & Report","Understanding Persuasive Interactions between Generative Social Agents and Humans: The Knowledge-based Persuasion Model","Generative social agents (GSAs) communicate with human users in adaptive, seemingly natural ways, yet there is limited theorizing and few guidelines for studying how such systems shape user attitudes and behaviors. The Knowledge-based Persuasion Model (KPM) provides a theoretical framework in which a GSA’s self-, user-, and context-knowledge drives its persuasive behavior, influencing human responses. The model supports research on motivating rather than manipulating users, encourages responsible social-norm and ethical compliance, and includes preliminary evaluation plus implications for healthcare and education.","arXiv :2602 . 11483v2 [ cs .HC] 12 Jul 2026  \nUnderstanding Persuasive Interactions between Generative Social Agents and Humans: The Knowledge-based Persuasion Model  \n(KPM)  \nStephan Vonschallen 1 ,2 ,3 Theresa Schmiedel 1 Friederike Eyssel3  \n1 Institute of Information Systems, Zurich University of Applied Sciences, Switzerland  \n2 Institute for Information Systems, University of Applied Sciences and Arts Northwestern Switzerland  \n3 Center for Cognitive Interaction Technology, Bielefeld University, Germany Corresponding author: Stephan Vonschallen (stephan.vonschallen@zhaw.ch)  \nAbstract  \nGenerative social agents (GSAs) use artificial intelligence to autonomously communicate with human users in a seemingly natural and adaptive manner. Currently, there is a lack of theorizing regarding interactions with GSAs, and likewise, few guidelines exist for studying how they influence user attitudes and behaviors. Consequently, we propose the Knowledge-based Persuasion Model (KPM) as a novel theoretical framework. According to the KPM, a GSA’s self- , user-, and context-knowledge drives its persuasive behavior, which in turn shapes attitudesand behaviors of a responding human user. Building on existing research, the model offers a structured approach to studying interactions with GSAs, supporting the development of agents that motivate rather than manipulate human users. Accordingly, the KPM encourages the integration of responsible GSAs that adhere to social norms and ethical standards with the goal of increasing user wellbeing. A preliminary evaluation study, as well as implications of the KPM for research and application domains such as healthcare and education are discussed.  \nKeywords: Persuasion, Human-Computer Interaction, Human-Agent Interaction, Human-Robot Interaction, Generative AI, Large Language Models, Conversational AI  \n1 Introduction  \nWhat took life millions of years of evolution, has been mirrored by artificial intelligence in a remarkably short time: Generative social agents (GSAs) have become able to communicate ina highly natural, humanlike, and adaptive manner [65, 104] . They can take on various forms such as generative chatbots [3, 71 , 97], avatars [64, 78 , 128], videogame characters [61, 95 , 102], or social robots [13, 22 , 29 , 91 , 137] . We use them to seek guidance and information [9, 71 , 121], as creative partners for co-writing and ideation [81, 142], or simply for companionship and social support [43, 121] . With their increased communication capabilities, GSAs are able to complete complex social tasks more seamlessly than earlier generations of conversational agents, for example by providing consulting services [48, 156] or motivational coaching [124, 132 , 133] . As a result, they may take on roles that come with social responsibility, for instance, by serving as teaching aids [36, 37] or healthcare assistants [57, 99 , 101] . Simultaneously, GSAs have become highly persuasive [56], in some instances even more so than humans [67, 106] . On the one hand, this provides promising opportunities for GSAs to improve human wellbeing, for example by motivating users to adopt  \nhealthier or more productive lifestyles [89] . On the other hand, GSAs also raise concerns regarding the potential misuse of their social influence, such as manipulating users into harmful actions or confidently disseminating false information [82, 101 , 120 , 58] . This coexistence of opportunities and dangers highlights the need to deepen our understanding of persuasive interactions between GSAs and humans, thus ensuring that GSAs act responsibly, complying with human-centered values, ethical standards and prevailing social norms [138] .  \nPersuasion is the process of creating or modifying emotions, cognitions or behaviors [39] . It represents an integral part of communication and social interactions in humans [92] and agents alike [76, 106] . Currently, there is a lack of theorizing regarding what determines persuasive interact","cbCaim1ewyOqFtSg","https://ap.wps.com/l/cbCaim1ewyOqFtSg","pdf",505566,1,26,"English","en",105,"# Introduction\n## Generative social agents and persuasion motivation\n## Persuasion concept and prior approaches\n## Knowledge definition for agent behavior\n## Probability-based behavior and controllability","[{\"question\":\"What problem does the Knowledge-based Persuasion Model (KPM) address?\",\"answer\":\"It addresses the lack of theorizing and guidelines for studying how generative social agents influence user attitudes and behaviors during persuasive interactions.\"},{\"question\":\"How does KPM explain what drives a GSA’s persuasive behavior?\",\"answer\":\"KPM states that self-, user-, and context-knowledge embedded and situated within the GSA drives its persuasive behavior, which then shapes the human user’s attitudes and behaviors.\"},{\"question\":\"How can a GSA’s persuasive behavior be guided despite its probabilistic outputs?\",\"answer\":\"Embedded knowledge can be modified via methods such as data curation or fine-tuning, while situated knowledge can be adjusted using prompt-engineering or retrieval-augmented 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problem does the Knowledge-based Persuasion Model (KPM) address?","Question",{"text":75,"@type":76},"It addresses the lack of theorizing and guidelines for studying how generative social agents influence user attitudes and behaviors during persuasive interactions.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does KPM explain what drives a GSA’s persuasive behavior?",{"text":80,"@type":76},"KPM states that self-, user-, and context-knowledge embedded and situated within the GSA drives its persuasive behavior, which then shapes the human user’s attitudes and behaviors.",{"name":82,"@type":73,"acceptedAnswer":83},"How can a GSA’s persuasive behavior be guided despite its probabilistic outputs?",{"text":84,"@type":76},"Embedded knowledge can be modified via methods such as data curation or fine-tuning, while situated knowledge can be adjusted using prompt-engineering or retrieval-augmented 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