Predicting new venture survival: A Twitter-based machine learning approach to measuring online legitimacy

Torben Antretter, Ivo Blohm, Dietmar Grichnik, Joakim Wincent

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)

Abstract

Research indicates that interactions on social media can reveal remarkably valid predictions about future events. In this study, we show that online legitimacy as a measure of social appreciation based on Twitter content can be used to accurately predict new venture survival. Specifically, we analyze more than 187,000 tweets from 253 new ventures’ Twitter accounts using context-specific machine learning approaches. Our findings suggest that we can correctly discriminate failed ventures from surviving ventures in up to 76% of cases. With this study, we contribute to the ongoing discussion on the importance of building legitimacy online and provide an account of how to use machine learning methodologies in entrepreneurship research.
Original languageEnglish
Article numbere00109
Peer-reviewed scientific journalJournal of Business Venturing Insights
Volume11
Issue numberJune
Pages (from-to)1-8
Number of pages8
ISSN2352-6734
DOIs
Publication statusPublished - 01.06.2019
MoE publication typeA1 Journal article - refereed

Keywords

  • 512 Business and Management

Fingerprint Dive into the research topics of 'Predicting new venture survival: A Twitter-based machine learning approach to measuring online legitimacy'. Together they form a unique fingerprint.

  • Cite this