The Need for Context
There is more data available at our fingertips today than there has ever been in human history, but how valuable is this data without any context? In fact, data can have many different effects based on the lens which someone views it through. In this way, data can be destructive as people are able to manipulate it to serve certain agendas.
In the course reading “Data Feminism,” the project GDELT, a project which attempted to assemble a massive set of all kinds of data, was used as a source by news outlet FiveThirtyEight. The news falsely reported that kidnappings in Nigeria were at an all-time high. Although the news source may have had good intentions, they used a source (GDELT) that was serving the agenda of “Big Dick Data.” According to the reading, “Big Dick Data” is the idea that large volumes of data should be gathered for the sole purpose of proving it can be gathered. Although this incident in Nigeria is just one example of a misuse of data, it is constantly seen in our news cycle.
As the Coronavirus pandemic swept through the United States in the past year, there have been a number of disputes about how it has been handled. From shutdowns to anti-maskers, the disagreements have been endless. One of the main disputes came in early September when the CDC reported that only about 6% of deaths in the pandemic were purely from COVID-19. The other 94% had other underlying ailments. This caused an uproar on social media because people didn’t view this statistic with context. The context here is that although these people may have had other illnesses, the ultimate cause of death was still COVID-19 and the majority of these people would be alive if it weren’t for the virus.
A big proponent of anti-shutdowns was ex-President Donald Trump, and he went as far as to send the tweet shown below.
This tweet is an example of using a bad context to view data. Here, Trump notes that the U.S. was reporting more cases because of more testing, but the reality was that the U.S. had to do more testing because we had so many cases which led to demand for more testing. So, it is not only important to use context when viewing data, but to also use a context that does the data justice.
References:
- Dale, Daniel, and Holmes Lybrand. “Fact Check: No, More Testing Isn’t the Reason US Coronavirus Case Numbers Are Getting Worse.” CNN, Cable News Network, 9 July 2020, www.cnn.com/2020/07/09/politics/fact-check-coronavirus-cases-donald-trump-testing/index.html.
- Yan, Holly, et al. “CDC Official Affirms Coronavirus Deaths Really Are Coronavirus Deaths.” CNN, Cable News Network, 2 Sept. 2020, www.cnn.com/2020/09/02/health/us-coronavirus-wednesday/index.html.