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This paper explores the effect of chatbot empathy and identity disclosure on willingness to donate (WTD) to a fundraising project and the psychological mechanism in the relationship. In a 3 (information-only vs. cognitive empathy vs. affective empathy) × 2 (chatbot vs. human identity) experiment, 496 US adults had a conversation about a fundraising event with one of six artificial intelligence-powered chatbots. The results revealed that neither chatbot empathy nor identity disclosure has a significant effect on WTD, rejecting the hypotheses. However, the data supported a significant interaction effect between chatbot empathy and identity disclosure on WTD. Moreover, the results suggested that the interaction effect between chatbot empathy and identity disclosure on WTD would be mediated through human likeness and social presence. This study suggests how empathy and human identity of chatbots should be applied with care to avoid the uncanny valley effect. [ABSTRACT FROM AUTHOR]

This paper presents a study about communicability of conversational interfaces (namely chatbots) under a semiotic perspective. A chatbot is a software system that allows you to simulate real conversations between devices and users by means of a conversational interface (CI). After introducing the chatbot concept, focusing on its advantages and issues, we will present two domains of use in which chatbot interfaces can be effective: healthcare and smart home. For carrying out simple tasks such as finding information or triggering operations, users need an easy-to-use and to an easy-to-learn system to communicate with. To face this, conversational interfaces represent the latest trend in the field of digital design. For studying the communicability aspects of a CI, we carried out a user test to compare traditional and chatbot interfaces. This paper aims at evaluating the benefits at the communicability level of a chatbot in comparison to traditional GUI for incrementing the effectiveness and efficacy of communication between users and the system specifically for users with poor attitude in using technologies. In details, we evaluated the communicability of two prototypes that can be used to solve simple tasks in order to favour user inclusion, including everyone with very little exposure to technologies. [ABSTRACT FROM AUTHOR]

There are great interests of designing research metrics and indices to measure the research impacts in research institutes. Unfortunately, most of those indices ignore critical design issues, e.g. the disparity between domains, the impact of journals or conferences in which papers are published, normalising the range of the index values to certain intervals, and the scalability of using the index to rank different research entities. In this paper, a new normalised fuzzy index, (NFindex), is proposed as a fuzzy-based research impact metric. The proposed index is a scalable index whose values are normalised to the percentage levels. NFindex achieves both inter-discipline normalisation and intra-discipline consistency. The capability of NFindex to achieve the inter-discipline normalisation enables fair comparison between different research domains regardless their nature in terms of influence and contribution to other research areas, e.g. natural science. Therefore, NFindex gives a universal normalised single-number metric that can be used by research institutes to solve the problem of inter-discipline scholar ranking. Moreover, it can help universal ranking of universities and research institutes according to their research capabilities and impacts. The obtained results, on diverse research areas, prove the potential of NFindex in terms of both intra-discipline consistency and inter-discipline normalisation. [ABSTRACT FROM AUTHOR]