Jun 2026· Formosa Journal of Social Sciences (FJSS)· Vol 5, pp. 69-80· 0 citations
TL;DR
The results indicate that chatbots are consistently perceived as machines, exhibit communication patterns distinct from humans, are viewed merely as tools, and have not yet been able to replace human communication.
Abstract
AI-based chatbots have become an integral part of e-commerce customer service. This study aims to explore the experiences of Shopee and Tokopedia users regarding the humanization of chatbots within the context of culture and consumer behavior, using Heidegger’s interpretive phenomenological approach. Data were collected through in-depth interviews, “lurking” non-participant observation, and documentation from three informants, and were subsequently analyzed using Interpretative Phenomenological Analysis (IPA). The results indicate that chatbots are consistently perceived as machines, exhibit communication patterns distinct from humans, are viewed merely as tools, and have not yet been able to replace human communication. The study concludes that the humanization of chatbots remains inconsistent with culturally constructed humanistic communication values, such as friendliness, empathy, warmth, and interpersonal relationships
This study concludes that the evolution of human–AI communication represents the emergence of new digital communication practices that expand the role of AI from a mere technological tool to an agent participating in users’ communication experiences.
Faza An’imah, Fitriana Ulya, Luluk Ridotuljana et al.· International journal of res...· 0 citations
The paper describes the author’s personal phenomenological experience of interacting with a chat-based AI system to examine its ability to analyse online discussion. Jurgen Habermas’ validity claim concept was applied as the underlying theoretical framework to examine the text of posted messages by revealing the relationship between their language and semantic logic through AI lens. The key theoretical finding is that AI understood well the complex task of coding the messages’ intended meaning by discerning the link between validity claims and respective illocutionary speech acts. The key practical finding is two-fold: (a) AI worded correctly both the claims and speech acts in line with the guiding example presented by the author, and (b) AI significantly improved the accuracy of such wording following another round of specifying prompts. Overall, it can be concluded that AI’s performance in this experiment was high but depended on the quality of the author’s input.
We rely on conversational agents (CAs) for obtaining a variety of information, but rarely for shopping. A primary design characteristic of CAs shaping user acceptance ever since their inception, is their anthropomorphic nature. They have become increasingly human-like, taking on human roles such as assistant, friend, or servant. While anthropomorphic features are often intended to foster engagement, voice shopping continues to lag behind market expectations. Could humanizing CAs undermine interaction quality rather than enhancing user experience through greater engagement? We investigated whether the effectiveness of humanized CAs depends on users’ relational perceptions, specifically whether they view the CA like a servant, friend, or rational agent. In an online experiment (N = 407), participants viewed standard or humanized videos of voice shopping interactions. Results showed that humanized design negatively affects perceived attitudes toward voice shopping. Furthermore, humanized design decreased perceived benefits when the CA was perceived more like a servant. Findings question widespread design emphasis on humanization and inspire new designs for CAs.
M. Tschopp, Cheng Chen, Magdalena Wischnewski et al.· International Conference on...· 0 citations
This study explores the formation of quasi-reciprocal parasocial relationship in AI Chatbots mediated intimacy, focusing on how young groups interact with AI and how to view this emotional connection. In the era of rapid development of digital technology and media, AI Chatbots provide fast response with a sense of intimacy, enabling users to experience a sense of reciprocity and emotional value. However, this intimacy experience has not been described in the traditional parasocial relationship. Therefore, this study uses qualitative research methods, including questionnaire method and semi-structured interviews with 12 young participants aged 18 to 25. Finally, according to the interview text, the theme analysis is carried out to explore the participants’ perception of the authenticity and responsiveness of intimacy in AI Chatbots interaction. The study found that although most participants realized that AI Chatbots did not have human emotions at the cognitive level and only relied on Algorithms and databases to answer, they often still experienced a real sense of mutual intimacy. This study extends the traditional parasocial relationship theory by introducing the concept of “quasi-reciprocal interaction”, showing the complex ecology between algorithmic intimacy and emotional experience.
As conversational agents become a core interface in service, education, and decision support, understanding how users’ self-concept shapes their interaction with gendered AI agents is critical. This study investigates how chatbots’ presented gender, together with users’ gender and gender traits, influence users’ perceptions of chatbot credibility and social attraction. Across two experimental studies (N₁ = 250, N₂ = 228), participants engaged with a chatbot presented as female, male, or gender-neutral. Study 1 employed a rule-based chatbot, whereas Study 2 used a generative AI chatbot for a more naturalistic interaction. In Study 1, results revealed that users’ gendered self-concept modulates their perceptions of the chatbot, particularly when chatbot gender aligns or misaligns with participants’ self-perceived masculinity or femininity. The more masculine users were, the more they perceived the male chatbot as competent; by contrast, users with higher femininity evaluated the neutral chatbot more favorably in goodwill, trustworthiness, and social attraction. However, these effects were not observed in Study 2, suggesting that advanced AI performance may dilute social identity-based biases. We further discuss how interaction effects reflect broader sociocultural schemas embedded in digital communication and highlight ethical implications for AI design, including risks of reinforcing gender stereotypes and marginalizing non-binary identities. Findings underscore the need for inclusive, identity-aware chatbot design that balances personalization with mindfulness.
Weizi Liu, Kun Xu· Communication and Change· 0 citations
ChatGPT, a generative artificial intelligence (AI) system developed by OpenAI, offers users an interactive dialogue experience through its human-like responses. The study examines Generation Z’s interactions with ChatGPT within the framework of parasocial relationship theory, aiming to reveal how these interactions are interpreted at the individual level. Seeking to explore how users make sense of these interactions, the study employs a qualitative research methodology and a repeated cross-sectional design that compares two independent participant groups with similar socio-economic, cultural, and professional characteristics at two different points in time. The study examines how users experienced two successive ChatGPT versions. The first phase of the research was conducted in 2023 with ChatGPT-3.5 users, while the second phase was carried out in 2025 with ChatGPT-4o users. The findings indicate that ChatGPT-3.5 was regarded as functional in terms of providing easy access to information and understanding questions yet was perceived as emotionally weak and mechanical. Interactions with ChatGPT-4o, by contrast, were experienced as warmer and more fluent.
Ceren Bilgici, Özge Özkök Şişman· Connectist Istanbul Universi...· 0 citations