Discovering Latent Topics of Digital Technologies From Venture Activities Using Structural Topic Modeling

This study attempts to explain the interplay between digital technologies and venture creation using structural topic modeling (STM), an automatic text analysis method, to detect latent topics related to digital technologies from large texts. The profile data of 133 344 U.S. companies from CrunchBase are analyzed. The data provide detailed descriptions in text about each company: what each company does. STM enables identification of topics related to digital technologies from the large company profile data. The findings identify those digital technologies that appear to have played the biggest role in the landscape of venture activities in the United States. The study also presents findings showing the temporal changes in such “digital” topics and the association of those topics with different industry sectors. The proposed analytical framework and the findings make contributions to the growing discussion about the intersection between digital technologies and new business creation.