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Human-Machine Communication Journal
Article . 2021 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Human-Machine Communication Journal
Article
License: CC BY NC ND
Data sources: UnpayWall
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Moving Ahead With Human-Machine Communication

Authors: Leopoldina Fortunati; Autumn Edwards;

Moving Ahead With Human-Machine Communication

Abstract

In this essay, we introduce the 10 articles comprising Volume 2 (2021) of Human-Machine Communication, each of which is innovative and offers a substantial contribution to the field of human-machine communication (HMC). As a collection, these articles move forward the HMC project by touching on four layers of important discourse: (1) updates to theoretical frameworks and paradigms, including Computers as Social Actors (CASA; Nass et al., 1996), (2) examination of ontology and prototyping processes, (3) critical analysis of gender and ability/disability relations, and (4) extension of HMC scholarship into organizational contexts. Building upon the insights offered by the contributing authors and incorporating perspectives coming from the historical, sociological, and semiotic (and hermeneutic) disciplines, we discuss challenges of applying CASA in HMC to suggest reframing in light of long-standing human experiences with automata, objective culture, narration (fiction), and symbols. Whereas CASA’s “old brains engage new media” formulation leads naturally to a focus on mindless versus mindful attribution processes, these hermeneutic and semiotic interpretations of robots/media as narrative texts and symbolic humans beg scholarly attention to issues of literacy and representation, respectively. Finally, we advance a series of justifications/calls for future research avenues.

Countries
Italy, United States
Keywords

Communication, P95-95.6, Communication Technology and New Media, T1-995, Robotics, Oral communication. Speech, Social and Behavioral Sciences, Technology (General)

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
31
Top 10%
Top 10%
Top 10%
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gold