Questionnaire: Music

Authors: Dimitri FASQUEL and Julien OLLIVIER

The goal of this survey is to make a typology of people who listen to music, concerning their interest for musical novelties, their degree of curiosity and the way they try to discover new musical things.

To realize our survey, we made a questionnaire composed of 30 points dealing with the uses, the material means, the different springs used to discover new music and the perception of music. 108 persons answered our questionnaire.

To begin, we perofrmed a Multiple Correspondence Analysis (MCA), then we choose to categorize the people interrogated with a Hierarchical Clustering on Principal Components (HCPC).

The first axis (6.756%) opposes the different degrees of musical knowledge. Indeed, it opposes people who are interested in music and who are looking for some uncommon ways to discover music to people who are not really interested in music and novelties.
The second axis (5.509%) opposes the kind of music people listen to: hard rock versus blues. It also associates degrees of knowledge and kind of media used to discover music. We can see that there are people who use only common ways to discover music, and some people who use more specialized ways.

The HCPC gave us four clusters, associated with different comportments:

  • The first cluster is composed of people for whom music is not essential. Their wish of discovering new music is not strong, whatever media is used to discover it
  • The second cluster is very specific. It is characterized by curious people. Not only are they music lovers, but they are also musicians. They use all the media to discover music, even the most specific ones
  • People in the third cluster are interested in music discovering but they only use very common ways to do it. Those access are quite easy, but limited
  • The last cluster is an average class, people are quite curious, they frequently discover new bands, using more spring of discovering than the first two clusters

Thanks to our survey and statistic tools, we managed to elaborate a real typology of music listeners, their comportments and how curious they are in front of novelties. We highlighted different clusters with their own characteristics.

Find here the data set and the R script:

The results of the ENMCA() function are the following:

Beware the results of HCPC() and ENMCA() are not quite the same since the data are ventilated and the method of classification is a bit different.