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Greussing, Esther ORCID logoORCID: https://orcid.org/0000-0001-8655-5119; Gaiser, Franziska ORCID logoORCID: https://orcid.org/0000-0001-9841-4102; Klein, Stefanie Helene ORCID logoORCID: https://orcid.org/0000-0002-7563-4548; Straßmann, Carolin ORCID logoORCID: https://orcid.org/0000-0002-9473-2944; Ischen, Carolin ORCID logoORCID: https://orcid.org/0000-0002-4135-1777; Eimler, Sabrina ORCID logoORCID: https://orcid.org/0000-0001-8944-2814; Frehmann, Katharina ORCID logoORCID: https://orcid.org/0000-0002-0226-5884; Gieselmann, Miriam ORCID logoORCID: https://orcid.org/0000-0002-4245-9237; Knorr, Charlotte ORCID logoORCID: https://orcid.org/0000-0001-6591-3781; Lermann Henestrosa, Angelica ORCID logoORCID: https://orcid.org/0000-0002-0733-9045; Räder, Andy ORCID logoORCID: https://orcid.org/0000-0002-1059-8363 und Utz, Sonja ORCID logoORCID: https://orcid.org/0000-0002-7979-3554 (2022): Researching interactions between humans and machines: methodological challenges. In: Publizistik, Vol. 67: pp. 531-554 [PDF, 439kB]

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Abstract

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.

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