Principal component analysis was utilized to elucidate nuanced aspects of the four themes and their links to well-being scores. Results showed that all four EDM event facets were positively associated with psychological and social well-being measures. These themes were then used as a basis for developing a questionnaire which explored relationships between scores on facets of EDM event attendance and measures of subjective, social, and psychological well-being (Study 2, n = 103).
Four main themes were identified, namely the importance of social, musical, and emotional experiences, and shared values at EDM event. Semistructured interviews with regular attendees of EDM events were undertaken and analyzed thematically (Study 1, n = 7). This exploratory mixed methods research draws influence from interdisciplinary research on EDM culture and psychological well-being research on music festivals that suggest EDM event attendance may have a positive influence on well-being. While an increasing amount of literature highlights the psychological well-being benefits of musical participation, research focusing on electronic dance music (EDM) event contexts remains scarce. This paper is expected to serve both as the proposal of a methodological framework and as a summary for researchers who haven’t contemplated the moral implications of similar technologies.
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A framework for experimentation and software design is proposed in order to achieve a systematic and operative utility leveling within logical contexts that allow the predictive use of meta-data and the design of mechanical means of recreating time. The concepts of extensive measurement, semantic bodies, existential coefficient, kathos, human bar-code and predictive censorship are introduced as complementary notions to work within the mainframe of epistemic encounters and the philosophical matrix of behavioral data. Breakthroughs and techniques in the area of Conversational Game Theory, phonetic indexing and semantics are proposed to frame linguistic units in the epistemological context that allows their location in a possible world. The mechanical qualities of language are theoretically examined to develop digital tools of text and speech recognition with a predictive functionality for situations of advanced problem-solving. This study is one of the first to look closely at the interactive relationship between the DJ and the nightclub audience through the lens of HCI, and our findings provide a number of guidelines for the design of new DJ- focused nightclub technologies. Despite the difficulties, DJs took a dim view of technology designed to let crowds exert more control over the music. DJs are adept at gathering visual information about the audience, despite poor lighting conditions and a heavy workload of selecting and mixing music. We found that DJs gather a wide variety of information about their audiences, and that this information is important to them as they plan and shape the evening's musical experience. We interviewed eleven DJs from several different cities, and asked them to discuss the ways that they interact with the audience, and the ways that they maintain and use awareness of the audience. To build this understanding, we carried out an interview study focusing on DJ-audience interactions. In order to design better technologies and systems in this area, it is important to start with an understanding of how nightclub interaction currently happens. However, these attempts have not always met with success.
Several researchers have recently proposed technology for crowd-and-DJ interactions in nightclub environments.