Artikel
An exploratory data analysis of the #crowdfunding network on Twitter
Together, social media and crowdsourcing can help entrepreneurs to attract external finance and early-stage customers. This paper investigates the characteristics and discourse of an issue-centered public on Twitter organized around the hashtag #crowdfunding through the lens of social network theory. Using a dataset of 2,732,144 tweets published during a calendar year, we use exploratory data analysis to generate insights and hypotheses on who the users in the #crowdfunding network are, what they share, and how they are connected to each other. In order to do so, we adopt a range of descriptive, content, network analytics techniques. The results suggest that platforms, crowdfunders, and other actors who derive income from the crowdfunding economy play a key role in creating the network. Furthermore, latent ties (strangers) play a direct role in disseminating information, investing, and sending signals to platforms that further raises campaign prominence. We also introduce a new type of social tie, the "computer as a social actor", previously unaddressed in entrepreneurial network literature, which play a role in sending signals to both platforms and networks. Our results suggest that homophily is a key driver for creating network sub-communities built around specific platforms, project types, domains, or geography.
- Language
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Englisch
- Bibliographic citation
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Journal: Journal of Open Innovation: Technology, Market, and Complexity ; ISSN: 2199-8531 ; Volume: 6 ; Year: 2020 ; Issue: 3 ; Pages: 1-22 ; Basel: MDPI
- Classification
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Management
- Subject
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crowdfunding
entrepreneurship
social network analysis
twitter
social media
strangers
computer as a social actor
CASA
- Event
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Geistige Schöpfung
- (who)
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Lynn, Theo
Rosati, Pierangelo
Nair, Binesh
Mac an Bhaird, Ciarán
- Event
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Veröffentlichung
- (who)
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MDPI
- (where)
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Basel
- (when)
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2020
- DOI
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doi:10.3390/joitmc6030080
- Handle
- Last update
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10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Lynn, Theo
- Rosati, Pierangelo
- Nair, Binesh
- Mac an Bhaird, Ciarán
- MDPI
Time of origin
- 2020