Chatting about the unaccepted: Self-disclosure of unaccepted news exposure behaviour to a chatbot

Conversational technologies such as chatbots have shown to be promising in eliciting self-disclosure in several contexts. Implementing such a technology that fosters self-disclosure can help to assess sensitive topics such as behaviours that are perceived as unaccepted by others, i.e. the exposure to unaccepted (alternative) news sources. This study tests whether a conversational (chatbot) format, compared to a traditional web-based survey, can enhance self-disclosure in the political news context by implementing a two-week longitudinal, experimental research design (n = 193). Results show that users disclose unaccepted news exposure significantly more often to a chatbot, compared to a traditional web-based survey, providing evidence for a chatbots’ ability to foster the disclosure of sensitive behaviours. Unlike our hypotheses, our study also shows that social presence, intimacy, and enjoyment cannot explain self-disclosure in this context, and that self-disclosure generally decreases over time

Developing a scale for human-likeness perceptions of conversational technologies

Conversational technologies are often implementing social or conversational cues. While these cues are used to mimic human behavior and make conversational agents appear as human-like as possible, consumers’ perceptions of the human-likeness of conversational technologies from a communication science perspective are not yet fully understood. To address this shortcoming, in this project we develop a field-specific conceptualization of human-likeness of conversational technologies, and develop a reliable and valid multidimensional measure based on existing theories and related scales

Doing it Together: Testing the Impersonal Impact Hypothesis in the Public Health Domain

The impersonal impact hypothesis states that news consumption leads to an increase of social concern, but not to an increase of personal concern, whereas the latter is most important for stimulating behaviour change. However, previous findings are mixed and mostly investigate private health behaviour. Here we, therefore, conceptually replicate these findings by studying a public health crisis: the case of the Covid-19 pandemic. The results of our longitudinal, five-wave study do not show support for the impersonal impact hypothesis, but rather seem to reveal the possibility of a personal impact hypothesis. That is, our findings show that news consumption increased participants’ personal concerns and to a lesser extent their societal concerns. News consumption furthermore indirectly affected adherence to governmental policy measures via these concerns. Additionally, participants adhered more to these measures when they believed they can make an incremental difference in stopping Covid-19 by adhering to Covid-19 policies (i.e., direct effect of participative beliefs). The belief of “doing it together” seems thus vital for policy adherence. Theoretical and practical implications are discussed

Future directions for chatbot research: an interdisciplinary research agenda

Chatbots are increasingly becoming important gateways to digital services and information—taken up within domains such as customer service, health, education, and work support. However, there is only limited knowledge concerning the impact of chatbots at the individual, group, and societal level. Furthermore, a number of challenges remain to be resolved before the potential of chatbots can be fully realized. In response, chatbots have emerged as a substantial research area in recent years. To help advance knowledge in this emerging research area, we propose a research agenda in the form of future directions and challenges to be addressed by chatbot research. This proposal consolidates years of discussions at the CONVERSATIONS workshop series on chatbot research. Following a deliberative research analysis process among the workshop participants, we explore future directions within six topics of interest: (a) users and implications, (b) user experience and design, (c) frameworks and platforms, (d) chatbots for collaboration, (e) democratizing chatbots, and (f) ethics and privacy. For each of these topics, we provide a brief overview of the state of the art, discuss key research challenges, and suggest promising directions for future research. The six topics are detailed with a 5-year perspective in mind and are to be considered items of an interdisciplinary research agenda produced collaboratively by avid researchers in the field