NFTeller: Dual-centric Visual Analytics for Assessing Market Performance of NFT Collectibles-Reference-Cited by-同舟云学术

NFTeller: Dual-centric Visual Analytics for Assessing Market Performance of NFT Collectibles

Published:2023-09-22 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 16th International Symposium on Visual Information Communication and Interaction
language:
Short-container-title:

Author:

Cao Yifan¹^ORCID,Xia Meng²^ORCID,Shigyo Kento³^ORCID,Cheng Furui⁴^ORCID,Yu Qianhang⁵^ORCID,Yang Xingxing⁶^ORCID,Wang Yang⁷^ORCID,Zeng Wei⁸^ORCID,Qu Huamin³^ORCID

Affiliation:

1. Individualized Interdisciplinary Program (CMA), The Hong Kong University of Science and Technology, Hong Kong

2. Computer Science Department, Carnegie Mellon University, USA

3. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong

4. Institute for Computing Platforms, ETH Zürich, Switzerland

5. The Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology, Hong Kong

6. The Hong Kong University of Science and Technology, Hong Kong

7. Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong

8. Thrust of Computational Media and Arts, The Hong Kong University of Science and Technology (Guangzhou), China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3615522.3615578

Reference25 articles.

1. Dynamic Public Opinion: Communication Effects over Time

2. Massimo Franceschet , Giovanni Colavizza , Blake Finucane , Martin Lukas Ostachowski , Sergio Scalet , Jonathan Perkins , James Morgan , Sebástian Hernández , 2020 . Crypto Art: A Decentralized View. Leonardo (2020), 1–8. Massimo Franceschet, Giovanni Colavizza, Blake Finucane, Martin Lukas Ostachowski, Sergio Scalet, Jonathan Perkins, James Morgan, Sebástian Hernández, 2020. Crypto Art: A Decentralized View. Leonardo (2020), 1–8.

3. Deep Residual Learning for Image Recognition

4. VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text

5. Min-Max Hash for Jaccard Similarity