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Visualizes the distribution of different violence risks in the emerging world based on scraped local headlines.

R 100.00%
webscapping regex natural-language-processing

risky-business's Introduction

Risky-Business

This project uses web scraping, regex and a labeling mechanism to uncover the relative distribution of different violence risks in the emerging world. The results include 822 risk headlines from 140 news sources. Just as Tom Cruise discovered in Risky Business, those seeking to venture into the unknown could find things get out of hand quickly if they’re not careful.


The report can be found here.

The code can be found here.


Sources:

Chong (2021) https://towardsdatascience.com/regular-expressions-clearly-explained-with-examples-822d76b037b4

The Economist (2021) https://www.economist.com/leaders/2021/07/31/unrest-and-economic-underperformance-stalk-the-emerging-world

UN (2020) https://www.un.org/en/un75/new-era-conflict-and-violence

World Bank (2022) https://www.worldbank.org/en/topic/fragilityconflictviolence/overview#1

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