{"title":"“从像个人一样说话到个性化:与对话代理的个性化、定期互动的影响”的勘误表[计算机]。嗡嗡声。Behav。:人造人(2024)100030]","authors":"Theo Araujo , Nadine Bol","doi":"10.1016/j.chbah.2025.100178","DOIUrl":null,"url":null,"abstract":"<div><div>As human-AI interactions become more pervasive, conversational agents are increasingly relevant in our communication environment. While a rich body of research investigates the consequences of one-shot, single interactions with these agents, knowledge is still scarce on how these consequences evolve across regular, repeated interactions in which these agents make use of AI-enabled techniques to enable increasingly personalized conversations and recommendations. By means of a longitudinal experiment (<em>N</em> = 179) with an agent able to personalize a conversation, this study sheds light on how perceptions – about the agent (anthropomorphism and trust), the interaction (dialogue quality and privacy risks), and the information (relevance and credibility) – and behavior (self-disclosure and recommendation adherence) evolve across interactions. The findings highlight the role of interplay between system-initiated personalization and repeated exposure in this process, suggesting the importance of considering the role of AI in communication processes in a dynamic manner.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100178"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Corrigendum to “From speaking like a person to being personal: The effects of personalized, regular interactions with conversational agents” [Comput. Hum. Behav.: Artificial Humans (2024) 100030]\",\"authors\":\"Theo Araujo , Nadine Bol\",\"doi\":\"10.1016/j.chbah.2025.100178\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>As human-AI interactions become more pervasive, conversational agents are increasingly relevant in our communication environment. While a rich body of research investigates the consequences of one-shot, single interactions with these agents, knowledge is still scarce on how these consequences evolve across regular, repeated interactions in which these agents make use of AI-enabled techniques to enable increasingly personalized conversations and recommendations. By means of a longitudinal experiment (<em>N</em> = 179) with an agent able to personalize a conversation, this study sheds light on how perceptions – about the agent (anthropomorphism and trust), the interaction (dialogue quality and privacy risks), and the information (relevance and credibility) – and behavior (self-disclosure and recommendation adherence) evolve across interactions. The findings highlight the role of interplay between system-initiated personalization and repeated exposure in this process, suggesting the importance of considering the role of AI in communication processes in a dynamic manner.</div></div>\",\"PeriodicalId\":100324,\"journal\":{\"name\":\"Computers in Human Behavior: Artificial Humans\",\"volume\":\"5 \",\"pages\":\"Article 100178\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in Human Behavior: Artificial Humans\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949882125000623\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in Human Behavior: Artificial Humans","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949882125000623","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Corrigendum to “From speaking like a person to being personal: The effects of personalized, regular interactions with conversational agents” [Comput. Hum. Behav.: Artificial Humans (2024) 100030]
As human-AI interactions become more pervasive, conversational agents are increasingly relevant in our communication environment. While a rich body of research investigates the consequences of one-shot, single interactions with these agents, knowledge is still scarce on how these consequences evolve across regular, repeated interactions in which these agents make use of AI-enabled techniques to enable increasingly personalized conversations and recommendations. By means of a longitudinal experiment (N = 179) with an agent able to personalize a conversation, this study sheds light on how perceptions – about the agent (anthropomorphism and trust), the interaction (dialogue quality and privacy risks), and the information (relevance and credibility) – and behavior (self-disclosure and recommendation adherence) evolve across interactions. The findings highlight the role of interplay between system-initiated personalization and repeated exposure in this process, suggesting the importance of considering the role of AI in communication processes in a dynamic manner.