Researching interactions between humans and machines: methodological challenges

Communication scholars are increasingly concerned with interactions between humans and communicative agents. These agents, however, are considerably different from digital or social media: They are designed and perceived as life-like communication partners (i.e., as “communicative subjects”), which in turn poses distinct challenges for their empirical study. Hence, in this paper, we document, discuss, and evaluate potentials and pitfalls that typically arise for communication scholars when investigating simulated or non-simulated interactions between humans and chatbots, voice assistants, or social robots. In this paper, we focus on experiments (including pre-recorded stimuli, vignettes and the “Wizard of Oz”-technique) and field studies. Overall, this paper aims to provide guidance and support for communication scholars who want to empirically study human-machine communication. To this end, we not only compile potential challenges, but also recommend specific strategies and approaches. In addition, our reflections on current methodological challenges serve as a starting point for discussions in communication science on how meaning-making between humans and machines can be investigated in the best way possible, as illustrated in the concluding section

First-principles modeling of the polycyclic aromatic hydrocarbons reduction

Density functional theory modelling of the reduction of realistic nanographene molecules (C42H18, C48H18 and C60H24) by molecular hydrogen evidences for the presence of limits in the hydrogenation process. These limits caused the contentions between three-fold symmetry of polycyclic aromatic hydrocarbon molecules and two-fold symmetry of adsorbed hydrogen pairs. Increase of the binding energy between nanographenes during reduction is also discussed as possible cause of the experimentally observed limited hydrogenation of studied nanographenes.Comment: 18 pages, 7 figures, accepted to J. Phys. Chem.