Musical networks : the case for a neural network methodology in advertisement music research
Hannelore Olivier · SUNScholar (Stellenbosch University) · 2005
ENGLISH ABSTRACT: Countless scientists had been struggling for centuries to find a significant connection between cognition, emotion and reasoning – resulting in today’s rather embarrassingly imperfect understanding of even the most basic human cognition. We should apprehend that it is unlikely that major breakthroughs in the Cognitive Sciences, Psychology, Sociology or the Medical Sciences will elucidate everything about the human brain and -behaviour in the very near future. Realizing this, it is realistic that we should transfer our attention to things that we do know and understand, and reconsider the power that lies in the integration of results and an interdisciplinary perspective in research. Using the tools we have to our disposal today – digital tools such as ANNs which did not exist a few decades before – this is actually readily viable today. This thesis demonstrates that it is possible to break the traditional boundaries that have periodically prevented the Humanities and the Natural Sciences to join forces towards a greater understanding of human beings. By using ANNs, we are able to merge data from any subfield within the Humanities and Natural Sciences in a single study. The results, interpretations and applications which could develop from such a study would certainly be more inclusive than those derived from research conducted in one or two of these fields in isolation. Sufficient evidence is provided in this dissertation to support a methodology which employs an artificial neural network to assist with decision-making processes related to the choice of advertisement music. The main objective of this endeavour is to establish the feasibility of combining data from many diverse fields, in the creation of an ANN that can be helpful in research regarding South African advertisement music. The thesis explores the notion that knowledge from many interdisciplinary study fields ought to play a leading role in the creation and assessment of effective, target-group-specific advertisement music. In obtaining this goal, it examines the probability of producing a computer-based tool which can assist people working in the advertising industry to obtain an educated match between product, consumer, and advertisement music. Taking a multidisciplinary point of view, the author suggests a methodology for the design of a digital tool in the form of a musical network model. It is concluded that, by using this musical network, it is indeed possible to guarantee a functional musically-paired commercial, which effectively addresses its target-group and has an appropriate emotional effect in support of the marketing goals of the advertising agent. The thesis also demonstrates that it is possible to gain new insights regarding a fairly unstudied discipline, without necessarily conducting new research studies in the specified field. The thesis proves that - by taking an interdisciplinary approach and by using ANNs - it is possible to attain new data that is scientifically valid, even in an unacknowledged field such as South African advertisement music. Although the scope of the thesis does not provide for the actual implementation of the musical network, the feasibility of the conceptual idea is thoroughly examined, and it is concluded that the theory in it’s entirely is definitely feasible, and can be implemented in a future study.