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Claremont Graduate University

Exploring the Influence of Startup Companies’ Social Networks on Funding with Machine Learning

Abstract

dc:description.abstract

<p>The significance of social networks facilitating startup success is undeniable in the modern startup landscape, characterized by rapid digitalization and an increasing emphasis on connectivity. This dissertation study assumes that a startup company's social network is critical in acquiring funding and promoting business growth. By combining social media data from LinkedIn, X, Facebook, Instagram, and YouTube with financial performance indicators from the Crunchbase database, this study aims to uncover patterns and attributes of social media networks that correlate with successful startup funding. Central to this research is the concept of social capital, defined as the aggregate value of all social networks and the benefits that arise from these networks. Specifically, this study examines how social capital translates into tangible funding gains for startup companies. This dissertation uses a quantitative research approach to explore the relationship between social media presence and startup funding outcomes. By identifying specific aspects of social network use that are important in securing funding, this research guides startups looking to leverage social media presence for growth and sustainability. The study contributes to the ongoing knowledge advancement regarding startups, digital connections, and the relevance of social networks, offering guidance on how social networks influence funding success for startup companies. Key findings indicate that the last funding amount and the number of investors consistently appear significant predictors of the total funding amount across different data subsets. The presence on multiple social media platforms, such as LinkedIn, Facebook, and X, identified significant predictor variables, including the number of LinkedIn followers, the number of years the Facebook page was active, whether the Facebook page is managed, and whether X likes to play significant roles in determining funding success. These insights underscore the importance of a strategic approach to building and maintaining a solid social media presence for startups seeking to maximize their funding potential.</p>

Degree

thesis:*
Name thesis:degree_name
Information Systems and Technology, PhD
Level thesis:degree_level
Open Access Dissertation
Discipline thesis:degree_discipline
Center for Information Systems and Technology
Year dc:date.available
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Cheng, Cindy
Contributors dc:contributor
  • June Hilton
  • Jeho Park

Subjects

dc:subject × 6

Identifiers

dc:identifier.*
Repository record dc:identifier
https://scholarship.claremont.edu/cgu_etd/892
OAI identifier oai:identifier
oai:scholarship.claremont.edu:cgu_etd-1914

Chain of custody

source
Harvested from
Claremont Graduate University
Base URL
scholarship.claremont.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Cheng, Cindy. Exploring the Influence of Startup Companies’ Social Networks on Funding with Machine Learning. Open Access Dissertation thesis, 2024. https://scholarship.claremont.edu/cgu_etd/892