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Diletta Mora

dblp:224/0089 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Games and playful interaction · 77% Human-AI interaction · 23%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Games and playful interaction › creative expression
music performance
0.412020
Automation and Creativity: A Case Study of DJs' and VJs' Ambivalent Positions on Automated Visual Software · CHI 2020

Methods — techniques the papers use, named apart from their topics

survey · 0.4interviews · 0.4
YearPublicationVenuePosition
2020 Automation and Creativity: A Case Study of DJs' and VJs' Ambivalent Positions on Automated Visual Software
abstract
Computerized solutions in the domain of creativity and expressive performance increasingly provide art and artists with exciting new opportunities. However, the combination of automation and creativity also raises controversies and resistance in some user groups. This paper considers the case of software-generated visuals in live music performance and tries to make sense of the ambivalent response given by its intended users (i.e., DJs and VJs). We carried out seven face-to-face interviews, an online survey (N = 102) and 25 interviews at a distance to unravel DJs' and VJs' positions on automated visual software. Four core controversies were eventually identified, gravitating around the implications of using such software on DJs' and VJs' identities as artists and on their competitive advantage in their activity sector. The conclusions reconnect these findings with the larger issue of understanding the users' responses to automation.
Anna Spagnolli, Diletta Mora, Matteo Fanchin, Valeria Orso, Luciano Gamberini
CHI2