Abstract

Initial coin offerings (ICOs) have been vulnerable to pump-and-dump schemes, where fraudsters spread false information on social media to inflate coin prices. However, initial exchange offerings (IEOs) are considered more reliable as exchanges conduct due diligence on projects. This study investigates the effectiveness of IEOs in mitigating pump-and-dump schemes by analyzing over 11,000 tweets posted by different accounts from 54 IEO projects one month prior to the IEO. We select 22 projects with at least 1000 tweets and use topic modeling to perform a descriptive analysis. We use botometer to produce a bot score for each tweet account and a pre-trained Bidirectional Encoder Representations from Transformers (BERT) model for sentiment analysis. We introduce penalized sentiment scores and interaction term and use an OLS regression model to identify the relationship between bot scores, sentiment values, and post-IEO performance. Our research finds that bot score is negatively associated with 30-day return and is positively associated with 30-day volatility, indicating the presence of pump-and-dump schemes in IEOs. We suggest that investors, exchanges, and regulators should take steps to assess the risks associated with IEOs and design appropriate interventions to prevent market manipulation.

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