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

Abstract

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.