A central problem in text-based chatbot research revolves around humanness: not only chatbots may reproduce fundamental aspects of being human, but also users may attribute humanlike features to chatbots. Humanness is paramount in human-chatbot conversations because it may profoundly impact the quality of the interaction: for example, when users expect that interactions with chatbots are similar to human conversations and these expectations are not met by the agent, they may easily become frustrated. This is particularly relevant in customer care, where efficient support is essential: here, unmet expectations about the chatbot’s humanlike capabilities can undermine customer satisfaction. In this article, we qualitatively analyzed 12,477 real-world exchanges with a task-based chatbot in the customer care domain, involving a total of 1,060 conversations. We conducted a single case study to define a preliminary theoretical model of humanness for chatbot technology. The study findings point to a novel conceptualization of humanness in customer-chatbot interaction, highlighting that it is multiple, contextual, modular, and dynamic. Moreover, the theoretical model that we propose explains that the kind of humanness attributed to a chatbot depends on the context in which people expect to interact, the objectives and needs that they aim to fulfill, and the cues that the chatbot exhibits: all these factors may change as the interaction evolves over time, and such changes may further affect the users’ ascriptions of humanness. Finally, we propose design implications of the model, like the need to create “context” and account for the plurality of humanness. © 2023 Taylor & Francis Group, LLC.

A central problem for chatbots in the customer care domain revolves around how people collaborate with the agent to achieve their own situated goals. The majority of the previous research, however, relied on experiments within artificial settings, rather than on observation of real-world interactions. Moreover, such research mostly analyzed users’ responses to communication breakdowns, rather than the wider collaboration strategies utilized during a conversation. In this paper, we qualitatively analyzed 12,477 real-world exchanges with a task-based chatbot using a Grounded Theory approach as a rigorous coding method to analyze the data. We identified two main aspects of collaboration, behavioral and conversational, and for each aspect we highlighted the different strategies that users perform to “work together”with the agent. These strategies may be utilized from the very beginning of the conversation or in response to misunderstandings in the course of ongoing interactions and may show different evolving dynamics. 

The outbreak of the COVID-19 has made apparent the importance of gaming technologies during crises and difficult life moments. However, studies exploring the role of commercial off-the-shelf video games during the pandemic are still limited. Moreover, research often focuses on a specific moment of the crisis. In this article, we investigate how playing commercial video games impacts on how players manage and understand the COVID-19 pandemic considered in its temporal evolution. We conducted a one-year-and-a-half longitudinal qualitative study by interviewing 16 participants who were living in Italy during the first pandemic lockdown, then involving a subgroup of them (N = 10) in a follow-up interview. Study findings show that playing not only supported escapism from a difficult reality, but also helped individuals counteract the sense of detachment from the “pandemic world”, encouraging reflection and supporting sense-making. These functions of video games varied as the pandemic unfolded. Based on these findings, we present a preliminary model of the role of video game technologies during moments of crisis and suggest design considerations on how video games could support people experiencing extremely difficult life moments. 

Wearable trackers are believed to enhance users’ self-knowledge, but their impact on the relationship that people have with their own bodies is relatively unexplored. This study aims to shed light on the potential of physiological data collected by a commercial wearable activity tracker to influence how users relate with their own bodies, specifically their body awareness, body image, body consciousness, and body surveillance. Additionally, the study seeks to determine whether this change in body perception improves or worsens the users’ relation with their own bodies. We recruited 321 first-time wearable users, including a control group. Participants in the experimental group (N = 225) completed a set of scales and questionnaires addressing body awareness and representations before and after wearing a Fitbit for four months, and 20 of them were further interviewed about their experience. The findings indicate that participants’ overall view of their bodies was not influenced by the device. However, the Fitbit did increase the awareness of bodily sensations, particularly for women. Moreover, we describe how participants made sense of the data displayed by the Fitbit, which was also used as an emotion-regulation tool. These results can contribute to the understanding of the impact of self-tracking technologies on the users’ perceptions of their own body and provide insights for future research in this field. © 2023 The Authors