Abstract

Minority sub-cultures have a strong influence on the intention, value, business conduct and decision making by entrepreneurs. In the past, little emphasis was given to the study of minority entrepreneurs who share different values and ideas from those who belong to the mainstream culture. Most of the existing studies of minority entrepreneurship have very limited coverage of the minority groups and sectors. Furthermore, they are affected by the bias and inefficiency problems due to the use of traditional survey instruments. To address these problems, we propose a text mining framework to identify the characteristics of minority entrepreneurs from unstructured text and multimedia contents. The output from our framework can be used to gain better understanding of the characteristics of the minority entrepreneurs in entrepreneurship research. This research contributes to the body of knowledge of data analytics in entrepreneurship studies by showing how text mining techniques can be used to study minority entrepreneurs from unstructured data.

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