2022
#SOS: India’s Tweets for Help
Country/area: India
Organisation: Reuters Graphics
Organisation size: Big
Publication date: 7/5/2021
Credit: Simon Scarr, Jitesh Chowdhury, Manas Sharma and Prasanta Kumar Dutta
Biography: The Reuters graphics team publishes visual stories and data. We typically cover all areas of the news, with content ranging from climate to financial markets. The team conceptualises, researches, reports, and executes many of the visual stories published.
Project description:
As the Delta variant swept through India, it brought the country’s healthcare system to its knees. The government struggled to cope with the burgeoning demand for hospital beds and oxygen cylinders. Desperate Indians turned to Twitter as the main platform for help as many were unable to rely on the healthcare system. This project took an in-depth look at the scale of suffering via social media data, revealing alarming trends in a host of Indian cities.
Impact reached:
The story was shared widely on social media and garnered a large volume of traffic as we looked at the unfolding crisis. This was particularly interesting as the story is very much about the effect of the very social platforms it was being shared and discussed upon.
Techniques/technologies used:
We used a Twitter scraping tool known as Twint that enabled us to comb through thousands of Tweets. We looked at how the situation escalated from April to early May 2021 which was the peak of the Delta wave in India. The opening animation was built in javascript. Charts were created in javascript and fine tuned in Adobe Illustrator and then ported back out via AI2HTML to be embedded into the web page.
We also built a custom scraper to track and collate oxygen data, revealing many hospitals were close to completely running out.
What was the hardest part of this project?
Because the nature of human language has nuances, it was initially hard to filter out words across the thousands of related tweets. A lot of work was needed to programatically clean the data. We also spent some time combing through the rest of the data manually, enabling us to find trends playing out in major urban areas of India.
What can others learn from this project?
Sometimes it is possible to take a very different and unique approach to an important story. In this case it was worth the extra data work to get this piece across the line and have a story that stood out from the typical reporting across other media outlets.
Project links:
graphics.reuters.com/HEALTH-CORONAVIRUS/INDIA-TWITTER/oakpekqlrpr/index.html
