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.

Sprache
Englisch

Erschienen in
Journal: Journal of Open Innovation: Technology, Market, and Complexity ; ISSN: 2199-8531 ; Volume: 6 ; Year: 2020 ; Issue: 3 ; Pages: 1-22 ; Basel: MDPI

Klassifikation
Management
Thema
crowdfunding
entrepreneurship
social network analysis
twitter
social media
strangers
computer as a social actor
CASA

Ereignis
Geistige Schöpfung
(wer)
Lynn, Theo
Rosati, Pierangelo
Nair, Binesh
Mac an Bhaird, Ciarán
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2020

DOI
doi:10.3390/joitmc6030080
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Lynn, Theo
  • Rosati, Pierangelo
  • Nair, Binesh
  • Mac an Bhaird, Ciarán
  • MDPI

Entstanden

  • 2020

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