Coronavirus News, Markets and AI : The COVID-19 Diaries

Coronavirus News, Markets and AI explores the analysis of unstructured data from coronavirus-related news and the underlying sentiment during its real-time impact on the world and on global financial markets, in particular. In an age where information - both real and fake - travels in the blink of an eye and significantly alters market sentiment daily, this book is a blow by blow account of economic impact of the COVID-19 pandemic.

The volume:  

• Details how AI driven machines capture, analyse and score relevant on-ground news sentiment to analyse the dynamics of market sentiment, how markets react to good or bad news across ‘short term’ and ‘long term’;
• Investigates what have been the most prevalent news sentiment during the pandemic, and its linkages to crude oil prices, high profile cases, impact of local news, and even the impact of Trump’s policies;
• Discusses the impact on what people think and discuss, how the COVID-19 crisis differs from the Global Financial Crisis of 2008, the unprecedented disruptions in supply chains and our daily lives;
• Showcases how easy accessibility to big data methods, cloud computing, and computational methods and the universal applicability of these tool to any topic can help analyse extract the related news sentiment in allied fields.

Accessible, nuanced and insightful, this book will be invaluable for business professionals, bankers, media professionals, traders, investors, and investment consultants. It will also be of great interest to scholars and researchers of economics, commerce, science and technology studies, computer science, media and culture studies, public policy and digital humanities.

List of Figures
List of Tables
Acknowledgements
About the Book
Introduction

Part I : The Method
Chapter 1 : How to Read this Book?
Chapter 2 : Reading Coronavirus News
Chapter 3 : Sentiment Analysis, Big Data and AI
Chapter 4 : Unstructured Data : How to Tame the Beast?

Part II : The Results
Chapter 5 : Ebbing in May : ‘Are We Celebrating Too Early?’
Chapter 6 : The Deadly April : ‘Blame Game and Search for a Coronavirus Vaccine’
Chapter 7 : Coronavirus Goes Global in March : ‘Oops… It is Getting Serious’
Chapter 8 : Build-up in February : ‘Come on, Do not Worry Too Much’

Part III : The Samples
Chapter 9 : Politics, Conspiracy Theories and Religion
Chapter 10 : The Coronavirus Pandemic’s Economic Impact
Chapter 11 : Disease, Devastation and Hope
Chapter 12 : Human Nature and the Impact on Normal Life
Chapter 13 : Bizarre, Funny and Fake News

Part IV : The Inference
Chapter 14 : Country Sentiment for Coronavirus News
Chapter 15 : COVID-19 has Turned the World Upside Down
Chapter 16 : What is Seen More Often in Coronavirus News?
Chapter 17 : How do We Use Sentiment Analysis? A Case Study
Chapter 18 : Conclusion

Index