Automatic detection of Fake Crowdfunding Projects
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Abstract
There may be fake information in some crowdfunding projects. However, it is difcult for crowdfunding platforms and investors to fnd fake information in crowdfunding projects. At present, many scholars have studied the methods for identifying fake information, but most of them studied how to distinguish fake information from news articles. Therefore, this research focuses on how to identify fake information that may exist in crowdfunding projects. The detection of fake crowdfunding projects includes functions such as keyword extraction, external knowledge extraction, and classification of real and fake projects. To identify possible fake information in the crowdfunding project, we need to understand more about the crowdfunding project by extracting the keywords of the crowdfunding projects. Therefore, this research compared TF-IDF, CKPE, YAKE, RAKE, TextRank4zh, FastTextRank, HarvestText, and BERT pre-training model methods. We used precision, recall, and F1 scores to measure the effectiveness of the keyword extraction method. Then, we obtained features for judging the authenticity of crowdfunding projects by extracting external knowledge of keywords. Finally, projects were classifed using a classifcation algorithm. The validity of this study for the classification of fake crowdfunding projects achieves 83.77% by the NB method in the dataset.
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