Browsing by Subject "Computer-aided text analysis (CATA)"

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Emotions and entrepreneurial finance: analysis of venture capitalists’ and business angels’ digital footprints on Twitter
(2024) Kaiser, Manuel; Kuckertz, Andreas; Kaiser, Manuel; Entrepreneurship Research Group, University of Hohenheim, Wollgrasweg 49, 70599, Stuttgart, Germany; Kuckertz, Andreas; Entrepreneurship Research Group, University of Hohenheim, Wollgrasweg 49, 70599, Stuttgart, Germany
Emotions are a central concept in previous entrepreneurship research, but this is mainly related to entrepreneurs and their entrepreneurial journey. However, venture capitalists (VCs) and business angels (BAs), two critical investors in the entrepreneurial finance literature, are essential actors in the entrepreneurial process. Still, little is known about investor emotions in this context. Therefore, in this study, we ask how venture capitalists differ from business angels in terms of their expressed emotions. To this end, we use an increasingly familiar research approach by examining the digital footprints of these investors on Twitter. For this purpose, we identify 822 investors from Crunchbase and analyze their 994,969 Tweets with Linguistic Inquiry and Word Count (LIWC) as a text analysis tool. Our results show that venture capitalists display more positive emotions on Twitter than angel investors, meaning that we find an association between VCs and emotional tone. Furthermore, in our post-hoc analysis, we explore further explanations for the differences between VC and BA. In doing so, we show differences in their expressed cognitive processes as well as in their communicated drivers. In both concepts, we find positive associations with the investor type of VC. To conclude this paper, we develop implications for practice and further research based on the results.