Tweet Based Reach Aware Temporal Attention Network for NFT Valuation

Ramit Sawhney, Megh Thakkar, Ritesh Soun, Atula Neerkaje, Vasu Sharma, Dipanwita Guhathakurta, Sudheer Chava


Abstract
Non-Fungible Tokens (NFTs) are a relatively unexplored class of assets. Designing strategies to forecast NFT trends is an intricate task due to its extremely volatile nature. The market is largely driven by public sentiment and “hype”, which in turn has a high correlation with conversations taking place on social media platforms like Twitter. Prior work done for modelling stock market data does not take into account the extent of impact certain highly influential tweets and their authors can have on the market. Building on these limitations and the nature of the NFT market, we propose a novel reach-aware temporal learning approach to make predictions for forecasting future trends in the NFT market. We perform experiments on a new dataset consisting of over 1.3 million tweets and 180 thousand NFT transactions spanning over 15 NFT collections curated by us. Our model (TA-NFT) outperforms other state-of-the-art methods by an average of 36%. Through extensive quantitative and ablative analysis, we demonstrate the ability of our approach as a practical method for predicting NFT trends.
Anthology ID:
2022.findings-emnlp.471
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2022
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Editors:
Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6321–6332
Language:
URL:
https://aclanthology.org/2022.findings-emnlp.471
DOI:
10.18653/v1/2022.findings-emnlp.471
Bibkey:
Cite (ACL):
Ramit Sawhney, Megh Thakkar, Ritesh Soun, Atula Neerkaje, Vasu Sharma, Dipanwita Guhathakurta, and Sudheer Chava. 2022. Tweet Based Reach Aware Temporal Attention Network for NFT Valuation. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 6321–6332, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
Tweet Based Reach Aware Temporal Attention Network for NFT Valuation (Sawhney et al., Findings 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.findings-emnlp.471.pdf
Software:
 2022.findings-emnlp.471.software.zip