Participatory narratives are compelling, at least partly because of their ability to help players suspend disbelief in the fictional world in which they engage. Game makers have used the phrase “This is Not a Game” (TINAG) to capture the willingness of players to buy into such narratives in ways that promote productive roleplaying and authentic engagement. Although TINAG has permeated the academic and popular literature on gaming and immersive narratives for decades, there has not been a scientific grounding for the term that provides researchers support for a more rigorous study of the topic. This article makes two primary contributions. First, it provides a definition of the Perception of TINAG based on a systematic literature review of 50 articles that define or describe critical characteristics of TINAG: The Perception of TINAG is a player’s acceptance that they are embedded in and able to influence a fictional story woven into the real world. Second, the paper develops and validates a survey instrument that researchers can use to measure the Perception of TINAG and its three unique components: (1) the player accepts that they are embedded in a fictional story, (2) the player believes their actions influence the narrative, and (3) the player perceives that the story is woven into the real world. We evaluated the instrument using exploratory factor analysis using expert reviewers and game players. We include a table of the articles describing TINAG and our final scale to facilitate future research.

Conversational agents (CAs) are becoming an increasingly common component in a wide range of information systems. A great deal of research to date has focused on enhancing traits that make CAs more humanlike. However, few studies have examined the influence such traits have on information disclosure. This research builds on self-disclosure, social desirability, and social presence theories to explain how CA anthropomorphism affects disclosure of personally sensitive information. Taken together, these theories suggest that as CAs become more humanlike, the social desirability of user responses will increase. In this study, we use a laboratory experiment to examine the influence of two elements of CA design—conversational relevance and embodiment—on the answers people give in response to sensitive and non-sensitive questions. We compare the responses given to various CAs to those given in a face-to-face interview and an online survey. The results show that for sensitive questions, CAs with better conversational abilities elicit more socially desirable responses from participants, with a less significant effect found for embodiment. These results suggest that for applications where eliciting honest answers to sensitive questions is important, CAs that are “better” in terms of humanlike realism may not be better for eliciting truthful responses to sensitive questions.

Automated human credibility screening is an emerging research area that has potential for high impact in fields as diverse as homeland security and accounting fraud detection. Systems that conduct interviews and make credibility judgments can provide objectivity, improved accuracy, and greater reliability to credibility assessment practices, need to be built. This study establishes a foundation for developing automated systems for human credibility screening.