"PocketBot Is Like a Knock-On-the-Door!": Designing a Chatbot to Support Long-Distance Relationships

Abstract

Many couples experience long-distance relationships (LDRs), and "couple technologies" have been designed to influence certain relational practices or maintain them in challenging situations. Chatbots show great potential in mediating people's interactions. However, little is known about whether and how chatbots can be desirable and effective for mediating LDRs. In this paper, we conducted a two-phase study to design and evaluate a chatbot, PocketBot, that aims to provide effective interventions for LDRs. In Phase I, we adopted an iterative design process through conducting need-finding interviews to formulate design ideas and piloted the implemented PocketBot with 11 participants. In Phase II, we evaluated PocketBot with eighteen participants (nine LDR couples)in a week-long field trial followed by exit interviews, which yielded empirical understandings of the feasibility, effectiveness, and potential pitfalls of using PocketBot. First, a knock-on-the-door feature allowed couples to know when to resume an interaction after evading a conflict; this feature was preferred by certain participants (e.g., participants with stoic personalities). Second, a humor feature was introduced to spice up couples' conversations. This feature was favored by all participants, although some couples' perceptions of the feature varied due to their different cultural or language backgrounds. Third, a deep talk feature enabled couples at different relational stages to conduct opportunistic conversations about sensitive topics for exploring unknowns about each other, which resulted in surprising discoveries between couples who have been in relationships for years. Our findings provide inspiration for future conversational-based couple technologies that support emotional communication.

Discovering the Hidden Facts of User-Dispatcher Interactions via Text-based Reporting Systems for Community Safety

“…The lack of emotional awareness in CAs might lead to difficulty in establishing rapport with users and awkwardness during conversations [Minhas et al(2022), Zheng et al(2021)]. An emotion-aware CA can quickly gain users' trust and elicit more information from them [Lee et al(2020)], thus significantly improving the efficiency of information gathering during safety incidents.…”