New(s) data for entrepreneurship research? An innovative approach to use Big Data on media coverage

Abstract

Although conventional register and survey data on entrepreneurship have enabled remarkable insights into the phenomenon, the added value has slowed down noticeably over the last decade. There is a need for fresh approaches utilising modern data sources such as Big Data. Until now, it has been quite unknown whether Big Data actually embodies valuable contributions for entrepreneurship research and where it can perform better or worse than conventional approaches. To contribute towards the exploration of Big Data in entrepreneurship research, we use a newly developed dataset based on publications of the German Press Agency (dpa) to explore the relationship between news coverage of entrepreneurship and regional entrepreneurial activity. Furthermore, we apply sentiment analysis to investigate the impact on sentiment of entrepreneurial press releases. Our results show mixed outcomes regarding the relationship between reporting of entrepreneurial events, i.e. media coverage, and entrepreneurial activity in German planning regions. At this stage, our empirical results reject the idea of a strong relationship between actual entrepreneurial activities in regions and the intensity of it being reported. However, the results also imply much potential of Big Data approaches for further research with more sophisticated methodology approaches. Our paper provides an entry point into Big Data usage in entrepreneurship research and we suggest a number of relevant research opportunities based on our results.