Unpacking the black box of ICO white papers: A topic modeling approach

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This study applies a novel topic modeling method to map Initial Coin Offerings’ (ICOs’) white paper thematic content to analyze its information value to investors. Using a sentence-based topic modeling algorithm, we determine and empirically quantify 30 topics in an extensive collection of 5,210 ICO white papers between 2015 and 2021. We find that the algorithm produces a semantically meaningful set of topics, which significantly improves the model performance in identifying successful projects. The most value-relevant topics concern the technical features of the ICO. However, we fnd that white paper’s informativeness substantially diminishes after the token is listed.

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05:21
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CHAUDHURI Ranjan - EMLV |
04:24
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BAG Surajit - EMLV |
06:06
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PANIBRATOV Andrei - |
03:43
With improving environmental consciousness and the growing demand for valuable resources, waste recycling has become an important concern. This work studies the profit of recyclers and platforms with a degree of trust-building in the reverse logistics system considering the following scenarios: online recycling platform builds trust or not under centralized and decentralized models. The results show that trust-building can effectively make more revenue for the system of the online recycling platform with enhanced demand if the cost of the trust-building construction is relatively low. The revenue-sharing contract is more profitable than the cost-sharing contract but fails to achieve optimization in the integrated setting. We find a new decision support tool for optimal strategies under different decision-making models.
YUAN Zhe - EMLV |

Medias of the same thematics

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