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This project investigates the impact of COVID-19 and lockdown on firm-level variables using a difference-in-differences approach, comparing Sweden and Norway. The outcome is an 11-page report.
A brief exploration of redditors' posts on r/wallstreetbets using quanteda
Built a python app with dynamic sentiment classification of tweets based on user input. Used NLP to build a model, Streamlit to deploy it as an app and Twint to perform webscraping from Twitter.
To find the Industry sinkers and swimmers of the COVID-19 pandemic
An overview of Japan's response to Covid-19; the lessons it learned from previous recessions!
Visualising twitter tweets related to covid19
**Here, we consider the relationship between data from the government's Furlough scheme, the Eat Out to Help Out scheme and how they relate to the grants the UK government has given out.**
My Submission for Economic Modeling
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