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Detecting Social Media Influencers of Startup Accelerators Using Social Network Analysis on Twitter

Drewnik, Damian (2023) Detecting Social Media Influencers of Startup Accelerators Using Social Network Analysis on Twitter.

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Abstract:The study focuses on detecting social media influencers and their power networks within the American technology startup Y Combinator accelerator. It aims to detect the major influencers amongst the people taking part in Y Combinator activities such as startup founders and accelerator employees. It uses social network analysis with a degree of centrality, betweenness of centrality, out-degree, in-degree, and eigenvector centrality as the primary variables. The main objective is to discover how people related to the accelerators are connected, using the Twitter social media platform. The research is expected to contribute to the scientific body of knowledge by presenting experimental results based on the Social Network Analysis approach. It will detect users that could be considered the most influential on the Twitter social media site in the Y Combinator Twitter space. It will also contribute to the startup accelerator's body of knowledge by discovering the social media structure of startup accelerators.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:50 technical science in general, 70 social sciences in general, 71 sociology, 85 business administration, organizational science
Programme:Business & IT BSc (56066)
Link to this item:https://purl.utwente.nl/essays/94411
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