This explorative study investigated (a) whether social attraction, self-disclosure, interaction quality, intimacy, empathy and communicative competence play a role in getting-acquainted interactions between humans and a chatbot, and (b) whether humans can build a relationship with a chatbot. Although human-machine communication research suggests that humans can develop feelings for computers, this does not automatically imply that humans experience feelings of friendship with a chatbot. In this longitudinal study, 118 participants had seven interactions with chatbot Mitsuku over a 3-week period. After each interaction participants filled out a questionnaire. The results showed that the social processes decreased after each interaction and feelings of friendship were low. In line with the ABCDE model of relationship development, the social processes that aid relationship continuation decrease, leading to deterioration of the relationship. Furthermore, a novelty effect was at play after the first interaction, after which the chatbot became predictable and the interactions less enjoyable.

Chatbots have several features that may stimulate self-disclosure, such as accessibility, anonymity, convenience and their perceived non-judgmental nature. The aim of this study is to investigate if people disclose (more) intimate information to a chatbot, compared to a human, and to what extent this enhances their emotional well-being through feelings of relief. An experiment with a 2 (human vs. chatbot) by 2 (low empathetic vs. high empathetic) design was conducted (N = 286). Results showed that there was no difference in the self-reported intimacy of self-disclosure between the human and chatbot conditions. Furthermore, people perceived less fear of judgment in the chatbot condition, but more trust in the human interactant compared to the chatbot interactant. Perceived anonymity was the only variable to directly impact self-disclosure intimacy. The finding that humans disclose equally intimate information to chatbots and humans is in line with the CASA paradigm, which states that people can react in a social manner to both computers and humans.

This research analyses the use of language-based strategies in human-chatbot interactions, namely the use of self-disclosure, question asking, expressions of similarity, empathy, humour, and the communication competence of the chatbot. This study aims to discover whether humans and a social chatbot communicate differently. Furthermore, we analyzed to what extent the chatbot’s expressions affect the human users’ expressions. A content analysis was conducted based on previously collected data from a longitudinal study, in which participants interacted seven times with chatbot Mitsuku over the course of three weeks. A randomly selected sample of 60 interactions was coded and results revealed that the participants self-disclosed more (intimately) and used more reciprocal self-disclosures, while the chatbot asked more questions, more reciprocal questions and more follow-up questions, expressed more similarity and humour. Moreover, the more questions the chatbot asked, the more the participants reciprocated these questions, and the more they self-disclosed. Our findings show that chatbots are programmed to gather information, by asking questions, to keep the conversation going, which elicits self-disclosure in human users. However, the self-disclosure was not reciprocated, which may hinder human-chatbot relationship formation.

This study examined which media people use on a day-to-day basis to communicate and whether tie strength influenced this media use. Furthermore, we analyzed whether online and offline interactions differ in perceived intimacy and whether tie strength impacts perceived interaction intimacy: 347 real interactions of 9 participants (3 male, 6 female) were analyzed; 172 online (WhatsApp, Facebook Messenger, email, SMS interactions) and 175 offline (recorded phone and face-to-face conversations). The results revealed that the participants communicated most frequently face-to-face or via WhatsApp, especially with strong ties. Furthermore, participants rated their interactions with strong ties as more intimate compared to weak-tie interactions. Our findings have implications for Social Information Processing theory, as our findings show that people are equally able to communicate intimate messages online and offline.