Data collection and forecast modeling: demand and price
Budget: $3,000 – $5,000 USD
Proof of concept for price prediction of NFT collections by analyzing data from the Opensea marketplace and social Twitter signals.
Collecting marketplace data through the Opensea API. Twitter data collection via Twint OSINT.
Purpose: Predict the floor/average price. Building a data pipeline. Achieve at least 0.85 accuracy. Prove the model's sustainability.
Additional: Determine what factors are influencing prices and trade volume the most.
References:
https://www.researchgate.net/publication/357987631_TweetBoost_Influence_of_Social_Media_on_NFT_Valuation
https://anyfty.medium.com/anyftys-first-results-in-nft-pricing-prediction-68c131501524
https://github.com/twintproject/twint
https://docs.opensea.io/reference/api-overview
Collecting marketplace data through the Opensea API. Twitter data collection via Twint OSINT.
Purpose: Predict the floor/average price. Building a data pipeline. Achieve at least 0.85 accuracy. Prove the model's sustainability.
Additional: Determine what factors are influencing prices and trade volume the most.
References:
https://www.researchgate.net/publication/357987631_TweetBoost_Influence_of_Social_Media_on_NFT_Valuation
https://anyfty.medium.com/anyftys-first-results-in-nft-pricing-prediction-68c131501524
https://github.com/twintproject/twint
https://docs.opensea.io/reference/api-overview