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Ananth, Anusha (2023) Role of Social Media in Start-ups Success using Machine Learning Approaches: Twitter. Masters thesis, Dublin, National College of Ireland.
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Abstract
The rise of start-ups has had a significant impact on the economy’s growth. A start-up grows through creativity, partnership, publicity, and so on. Start-ups utilize social media platforms to publicize their ideas and goods as a result of the internet explosion over the last decade. A business is referred to as a ”unicorn” if it surpasses the billion-dollar milestone. Twitter, WhatsApp, Facebook, Instagram, and other popular social media networks. Sometimes financing is reliant on client tweets or feedback. The major purpose of this research is to ascertain the influence of tweets on start-up investment. The project’s principal purpose is to develop machine learning and data mining algorithms that can be used for large start-up funding datasets to gain insights that will assist venture capitalist specialists in offering timely insights regarding series investments. A hybrid strategy of feature selection utilizing the K-Fold Statistical technique, regression, and neural network approaches was built to identify relevant factors for the forecast of start-up series funding. For each model, the Root Mean Squared Error is generated and used to evaluate its performance. The hybrid technique extracted 30 funding-related characteristics from Twitter data, and the Recursion Neural Network (RNN) produced a Root Mean Squared Error (RMSE) of 0.65 by outperforming the other models.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Milosavljevic, Vladimir UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning H Social Sciences > HD Industries. Land use. Labor > New Business Enterprises Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Websites > Online social networks T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Online social networks |
| Divisions: | School of Computing > Master of Science in Data Analytics |
| Depositing User: | Tamara Malone |
| Date Deposited: | 17 May 2023 09:39 |
| Last Modified: | 17 May 2023 09:39 |
| URI: | https://norma.ncirl.ie/id/eprint/6562 |
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