Risk disclosure and entrepreneurial resource acquisition in crowdfunding digital platforms: Evidence from digital technology ventures

Huo, Hong; Wang, Chen; Han, Chunjia; Yang, Mu; Shang, Wen-Long

doi:10.1016/j.ipm.2024.103655

Cited by 2 publications

(1 citation statement)

References 57 publications

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“…Using data from a wide span of time, the research builds a solid foundation for the development of applications that are more adaptive and responsive to future user needs. The application of text mining is driven by trial-and-error experiments based on the experience of previous researchers (Huo et al, 2024). While relative data mining methodologies have long been used (e.g.…”

Section: Methodsmentioning

confidence: 99%

Text Mining Algorithm Naive Bayes Classifier to Improve Quality Sentiment Analysis Passport Mobile Application

Syahrin,

Wilonotomo,

Mulyawan

et al. 2024

Preprint

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Mobile Passport is an application that can be used as a digital service for people in Indonesia to apply for a new passport and an official online passport replacement from the Directorate General of Immigration replacing APAPO (Online Passport Service Application). User reviews of the Mobile Passport application are the output of big data generated as a result of the Internet of Things. The problem formulation in this research is how the implementation of the Naive Bayes text mining classifier algorithm can analyze the reviews contained in the Mobile Passport application as well as the accuracy, precision and recall values. This research uses the KDD (Knowledge Discovery and database) method which consists of data selection, data preprocessing, transformation, data mining, and evaluation using the R Studio tool. The resulting knowledge and information from this process is used as a useful knowledge base in decision making. The Naive Bayes classifier algorithm method in this research is used because of its reliability in handling data quickly and accurate predictions based on class probabilities, thus enabling research to obtain consistent and reliable results.

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Section: Methodsmentioning

confidence: 99%

Text Mining Algorithm Naive Bayes Classifier to Improve Quality Sentiment Analysis Passport Mobile Application

Syahrin,

Wilonotomo,

Mulyawan

et al. 2024

Preprint

View full text Add to dashboard Cite

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Bibliometric Analysis of the Machine Learning Applications in Fraud Detection on Crowdfunding Platforms

Cardona,

Guzmán-Luna,

Restrepo-Carmona

2024

JRFM

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Crowdfunding platforms are important for startups, since they offer diverse financing options, market validation, and promotional opportunities through an investor community. These platforms provide detailed company information, aiding informed investment decisions within a regulated and secure environment. Machine learning (ML) techniques are important in analyzing large data sets, detecting anomalies and fraud, and enhancing decision-making and business strategies. A systematic review employed PRISMA guidelines, which studied how ML improves fraud detection on digital crowdfunding platforms. The analysis includes English-language studies from peer-reviewed journals published between 2018 and 2023 to analyze the pre- and post-COVID-19 pandemic. The findings indicate that ML techniques such as Random Forest, Support Vector Machine, and Artificial Neural Networks significantly enhance the predictive accuracy and utility of tax planning for startups considering equity crowdfunding. The United States, Germany, Canada, Italy, and Turkey do not present statistically significant differences at the 95% confidence level, standing out for their notable academic visibility. Florida Atlantic and Cornell Universities, Springer and John Wiley & Sons Ltd. publishing houses, and the Journal of Business Ethics and Management Science magazines present the highest citations without statistical differences at the 95% confidence level.

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Risk disclosure and entrepreneurial resource acquisition in crowdfunding digital platforms: Evidence from digital technology ventures

Cited by 2 publications

References 57 publications

Text Mining Algorithm Naive Bayes Classifier to Improve Quality Sentiment Analysis Passport Mobile Application

Text Mining Algorithm Naive Bayes Classifier to Improve Quality Sentiment Analysis Passport Mobile Application

Bibliometric Analysis of the Machine Learning Applications in Fraud Detection on Crowdfunding Platforms

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