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Predicting new venture survival: A Twitter-based machine learning approach to measuring online legitimacy
University of St.Gallen, St.Gallen, Switzerland.
University of St.Gallen, St.Gallen, Switzerland.
University of St.Gallen, St.Gallen, Switzerland.
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering. University of St.Gallen, St.Gallen, Switzerland;Hanken School of Economics, Helsinki, Finland.ORCID iD: 0000-0002-8770-8874
2019 (English)In: Journal of Business Venturing Insights, ISSN 2352-6734, Vol. 11, article id e00109Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 11, article id e00109
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Other Engineering and Technologies not elsewhere specified
Research subject
Entrepreneurship and Innovation
Identifiers
URN: urn:nbn:se:ltu:diva-72881DOI: 10.1016/j.jbvi.2018.e00109Scopus ID: 2-s2.0-85059509620OAI: oai:DiVA.org:ltu-72881DiVA, id: diva2:1288396
Note

Validerad;2019;Nivå 1;2019-02-13 (johcin)

Available from: 2019-02-13 Created: 2019-02-13 Last updated: 2019-02-13Bibliographically approved

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Wincent, Joakim

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