Mining and Modeling Both Association Patterns and Determinants for the Attendance of Performing Arts Activities

ABSTRACT

The literature has explored related issues about the audience of performing arts activities with empirical investigations using various analytical approaches in different countries. Certain studies have concentrated on the univorous-omnivorous framework, aiming to examine if people participate in a wide range of performing arts genres or if they exhibit a more distinct preference for a specific type, while others explore what factors may influence individuals’ participation in different types of performing arts activities. This paper analyzes data from a survey that focuses on related issues about the attendance of performing arts events in three cities located in northern Taiwan. Performing arts in Taiwan are classified into four categories: music, dance, contemporary drama, and traditional theater. We mine patterns about how the audiences consume various type combinations of performing arts events through the association rule as well as identify determinants related to events’ attendances. Both the association mining approach and appropriate statistical modeling analytics are applied to achieve said purposes.

KEYWORDS:

• Association rule mining
• audience characteristics
• log-linear regression model
• multivariate probit regression model
• performing arts attendance
• univorous-omnivorous framework

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the Ministry of Science and Technology in Taiwan [MOST111-2118-M-004-004].