Chasing the Chatbots: Directions for Interaction and Design Research

Big tech-players have been successful in pushing the chatbots forward. Investments in the technology are growing fast, as well as the number of users and applications available. Instead of driving investments towards a successful diffusion of the technology, user-centred studies are currently chasing the popularity of chatbots. A literature analysis evidences how recent this research topic is, and the predominance of technical challenges rather than understanding users’ perceptions, expectations and contexts of use. Looking for answers to interaction and design questions raised in 2007, when the presence of clever computers in everyday life had been predicted for the year 2020, this paper presents a panorama of the recent literature, revealing gaps and pointing directions for further user-centred research

Human-machine networks: Towards a typology and profiling framework

© Springer International Publishing Switzerland 2016. In this paper we outline an initial typology and framework for the purpose of profiling human-machine networks, that is, collective structures where humans and machines interact to produce synergistic effects. Profiling a humanmachine network along the dimensions of the typology is intended to facilitate access to relevant design knowledge and experience. In this way the profiling of an envisioned or existing human-machine network will both facilitate relevant design discussions and, more importantly, serve to identify the network type. We present experiences and results from two case trials: a crisis management system and a peerto- peer reselling network. Based on the lessons learnt from the case trials we suggest potential benefits and challenges, and point out needed future work

A personalized and context-aware news offer for mobile devices

For classical domains, such as movies, recommender systems have proven their usefulness. But recommending news is more challenging due to the short life span of news content and the demand for up-to-date recommendations. This paper presents a news recommendation service with a content-based algorithm that uses features of a search engine for content processing and indexing, and a collaborative filtering algorithm for serendipity. The extension towards a context-aware algorithm is made to assess the information value of context in a mobile environment through a user study. Analyzing interaction behavior and feedback of users on three recommendation approaches shows that interaction with the content is crucial input for user modeling. Context-aware recommendations using time and device type as context data outperform traditional recommendations with an accuracy gain dependent on the contextual situation. These findings demonstrate that the user experience of news services can be improved by a personalized context-aware news offer

Users’ design feedback in usability evaluation: a literature review

Abstract As part of usability evaluation, users may be invited to offer their reflections on the system being evaluated. Such reflections may concern the system’s suitability for its context of use, usability problem predictions, and design suggestions. We term the data resulting from such reflections users’ design feedback. Gathering users’ design feedback as part of usability evaluation may be seen as controversial, and the current knowledge on users’ design feedback is fragmented. To mitigate this, we have conducted a literature review. The review provides an overview of the benefits and limitations of users’ design feedback in usability evaluations. Following an extensive search process, 31 research papers were identified as relevant and analysed. Users’ design feedback is gathered for a number of distinct purposes: to support budget approaches to usability testing, to expand on interaction data from usability testing, to provide insight into usability problems in users’ everyday context, and to benefit from users’ knowledge and creativity. Evaluation findings based on users’ design feedback can be qualitatively different from, and hence complement, findings based on other types of evaluation data. Furthermore, findings based on users’ design feedback can hold acceptable validity, though the thoroughness of such findings may be questioned. Finally, findings from users’ design feedback may have substantial impact in the downstream development process. Four practical implications are highlighted, and three directions for future research are suggested