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Data Science for Web3

You're reading from Data Science for Web3

Product type Book

Published in Dec 2023

Publisher Packt

ISBN-13 9781837637546

Pages 344 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Gabriela Castillo Areco

Table of Contents (23) Chapters

Preface

1. Part 1 Web3 Data Analysis Basics

2. Chapter 1: Where Data and Web3 Meet

3. Chapter 2: Working with On-Chain Data

4. Chapter 3: Working with Off-Chain Data

5. Chapter 4: Exploring the Digital Uniqueness of NFTs – Games, Art, and Identity

6. Chapter 5: Exploring Analytics on DeFi

7. Part 2 Web3 Machine Learning Cases

8. Chapter 6: Preparing and Exploring Our Data

9. Chapter 7: A Primer on Machine Learning and Deep Learning

10. Chapter 8: Sentiment Analysis – NLP and Crypto News

11. Chapter 9: Generative Art for NFTs

12. Chapter 10: A Primer on Security and Fraud Detection

13. Chapter 11: Price Prediction with Time Series

14. Chapter 12: Marketing Discovery with Graphs

15. Part 3 Appendix

16. Chapter 13: Building Experience with Crypto Data – BUIDL

17. Chapter 14: Interviews with Web3 Data Leaders

18. Index

Why subscribe?

19. Other Books You May Enjoy

Appendix 1

1. Appendix 2

2. Appendix 3

Adding news to our dataset

A professor once mentioned that in the crypto world, news takes only five minutes to impact the price of an asset.

News is not only important for its effect on prices but marketing teams may also request analysis of the social impact of a brand, a campaign, or a product, or it may be necessary to source an algorithm, among other applications. For that purpose, data scientists need news formatted for analysis.

As of today, there is a dedicated source named CryptoPanic, a data aggregator that specifically indexes news relevant to the Web3 ecosystem. The link to the website is https://cryptopanic.com/.

Its data can be consumed through an API and the API key is available upon registration.

On the main page, go to the Sign In tab on the left menu:

Figure 3.16 – An overview of the CryptoPanic main view

Figure 3.16 – An overview of the CryptoPanic main view

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Authors (1)

Gabriela Castillo Areco

Gabriela Castillo Areco holds an M.Sc. in big data science from the TECNUM School of Engineering, University of Navarra. With extensive experience in both the business and data facets of blockchain technology, Gabriela has undertaken roles as a data scientist, machine learning analyst, and blockchain consultant in both large corporations and small ventures. She served as a professor of new crypto businesses at Torcuato di Tella University and is currently a member of the BizOps data team at IOV Labs.

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