Two journalism professors at the City University of New York (CUNY) introduced the use of data through a few case studies during the one-hour interactive session “Power in Numbers: Building Compelling Data-Driven Stories.”
Professor Sandeep Junnarkar, who’s also a consulting newsroom trainer at Bloomberg News, started off this session with an introduction to digital journalism. It’s currently the most popular contemporary form of news media. In one of his slides, Junnarkar listed the goal of journalism as the following: “inform and clarify, reveal hard to see patterns and trends, and show the scope of an issue.”
He first showed how technology can channel information to the audiences. One example is the use of natural language processing. It enables computers to support and manipulate speech. Using the natural language processing function, Junnarkar found that Paul Ryan, the former speaker of the House, used the word “spending” 95% less once former president Donald Trump was elected.
Junnarkar went on to further break down the digital journalism basics through a few case studies. He brought up a Bloomberg article that showed racial bias in Amazon’s delivery services. According to Junnarkar, analysts designed an automated program inputting 45,000 ZIP codes into the search engine of Amazon delivery. The time span between each ZIP code entry varied from 45 seconds to one minute, so as not to be found out by Amazon administrators.
After analyzing six big cities, Bloomberg analysts concluded that same-day delivery services predominately excluded ZIP codes with higher percentages of Black residents to varying degrees.
After this article was published, Amazon adjusted its delivery services so more Black communities could also enjoy same-day delivery. At the same time, Amazon also took down the search page for its delivery.
“When people think about data journalism, they also think about numbers or spreadsheets. However, data journalism is not about that, but something you really can turn into something interesting and something people work on,” said Junnarkar.
Later, the other professor, Jere Hester talked about one news story published by The City, which detailed changing the coronavirus tracker. At the early stage of the coronavirus outbreak, The City realized that the traditional virus tracker may not have fully reflected the real case count, since there was only a small fraction taking COVID-19 tests at the hospital. To get more accurate data, The City stopped showing test data and presenting the case rate by ZIP code. Instead, the paper incorporated hospitalization rates, ICU capacity, deaths, and the vaccination rate into the new tracker.
“What we can do over the data is that, even though these are existing numbers, we can use them to bring insights and to bring actions,” Hester concluded.