There is an art to data visualization. A designer must understand the presentation methods that lead to corruption or misleading ideals while also trying to create hopeful and curious information for the audience. Presenters can also be led to cherry-pick, which involves selecting and revealing only certain parts of a data set (Tufte, 2006). The goal of cherry-picking is to advance the opinion or thoughts of the presenter.
Cherry-picking can be spotted by using some ideas from Janice Morse, who wrote Cherry-Picking: Writing from Thin Data in the Qualitative Health Research journal in 2010. Morse explains that a viewer can recognize cherry-picked data if the sample size of the research is small with a tight scope. Having a large sample size with a wealth of data is more reliable than a small sample size.
Another way to recognize cherry-picking is when the viewer believes there are missing categories in the research. This can be caused if the researched is too specific when creating categories or setting the boundaries for a study to tight. Morse explains that the worst case of cherry-picking can come from a lazy researcher. If a researcher has selected the most interesting or the most unusual quotations from the study, cherry-picking has been utilized. (Morse, 2010).
In relation to my data visualization project about the impacts of the COVID-19 pandemic the film/entertainment industry, I will be looking at the large increase of Netflix subscriptions since the pandemic began in March. As the researcher, I would be cherry-picking if I did not include data from other online streaming services and the impact COVID-19 had on them. I would not be able to say “Netflix was the most widely used online streaming service during the pandemic” unless I compared the data from other online streaming services and their subscriptions.
Tufte explains the process of data collection to the final published report. First, the researcher observes and collects raw data. For my data visualization final project, I have asked myself questions and observed something that is happening in the world.
What does online streaming look like before, during and after the pandemic, specifically, Netflix?
How has the pandemic impacted online streaming for movies that were originally for release in movie theaters?
Are people willing to pay to watch movies on a online streaming service like Disney+?
The next step in the data collection to final report process is “evidence reduction, construction and representation” (Tufte, 2006). This middle step requires the researcher to analyze the data he or she has collected so that they can advance into the final step of presenting the reports/data in charts, graphs, images, numbers or words.
Related to my research/data viz project, I looked into Netflix’s dramatic rise as the pandemic began. According to the BBC and Netflix’s quarterly reports, Netflix had almost 16 million people create new accounts during the first three months of 2020. Comparatively, the online streaming giant had almost half of that number in the final months of 2019.
But, Netflix also had to halt almost of their productions due to the pandemic, which were happening all around the world. In addition, currencies around the world have also lost some of their value, which means the new international subscribers aren’t worth as much to Netflix as they would have been before the global crisis (BBC, 2020).
To add, as the U.S. begins to slowly reopen, Netflix predicts new subscriptions will decline. Netflix also believes future subscribers could decrease due to back-up of shows and movies that haven’t filmed yet.
Zoe Thomas, BBC News Technology Reporter, explains that Netflix faces a steady competition against Disney+ and Amazon Prime, which seem to have a library of unreleased content to bring in new subscribers. Thomas also reports that Europe, the Middle East and Africa recorded seven million new members to Netflix, which was the largest group of new subscribers worldwide.
Netflix is an American company, so new subscribers have been lagging in recent quarters in the States and Canada, but during the lockdown, 2.3 million new viewers logged on, as compared to 550,000 in the final months of 2019. Profits almost doubled compared to the same time last year from $344 million to $709 million (Thomas, 2020).
Statistics before the pandemic – Worldwide growth for Netflix (Kindig, 2020)
190 OTT providers in the U.S. (over-the-top streaming platform)
Netflix claims 87% of OTT households in the U.S.
For my project, I have a few different ideas for story-telling and aesthetics. I can imagine a bucket of popcorn that represents all of the different OTT providers in the U.S. and how Netflix holds a massive spot with 87% of U.S. households. I also imagine a world map that shows the increase in Netflix subscriptions during the pandemic. In addition, I envision a film reel maneuvering its way throughout the visual.
The audience is anyone who is interested in the growth and decline of businesses during a crisis. It is anyone who enjoys sitting at home watching movies and television. My audience is anyone who has binge-watched a few shows during this global health crisis. The goal of my visual story is to keep the viewers entertained and informed. How has the pandemic affected some of the biggest businesses in Hollywood? Are people turning over the movie ticket stubs and grabbing their remotes to turn on their favorite online streaming service? The entertainment business, specifically online streaming content, has been changing since the inception of YouTube and later, Netflix – the red envelopes we used to receive in the mail with movies in them quickly transformed into award-winning pieces of content for viewers across the globe.
The goal of this project is to inform viewers about the changing landscape in the entertainment business, and how it has been directly related to the COVID-19 pandemic.
References
Kindig, B. (2020, Jan. 1). Netflix stock: Unshakeable long term. Retrieved from https://www.forbes.com/sites/bethkindig/2020/01/20/netflix-stock-first-mover-is-unshakeable-long-term/#43806c785abb
Morse, J. (2010). “Cherry-Picking:” Writing from thin data. Qualitive Health Research Journal. 20 (1), 3. Sage Publishers.
Thomas, Z. (2020). Netflix gets 16 million new sign ups thanks to lockdown. BBC. https://www.bbc.com/news/business-52376022
Tufte, E. (2006). Beautiful Evidence. Graphics Press.
Tufte, E. (1997). Visual Explanations. Graphics Press.
MAGGIE PRUITT 