Are The Grammys Rigged?: About The Project

In the Spring of 2024, I took a data storytelling class where we were tasked to gather data and create a story from it. The project had a second part where we were tasked to write an analysis of our project. This analysis describes the process we utilized when creating the story, the skills we learned, and the sources we used.

Are The Grammys Rigged?

An analysis of the winners and nominees from the past two years

The Grammys are one of the biggest events in the music world and bring in thousands of viewers. The public tends to use this event as a way to see what the best music was for the past year. After hearing artists talk negatively about the awards show and hearing some claims that it is rigged, we decided to gather data and answer the question: Are the Grammys Rigged?

About the Project

Where did the project originate?

The brainstorming process

When brainstorming ideas for this project, we were immediately drawn to analyzing and comparing the results of the 2023 and 2024 Grammy Awards. The 2024 Grammys had recently passed and was still being talked about regularly which made it an easy decision. Initially, we struggled to find an angle for the story but after gathering and analyzing the data, the story began to form itself.

Building The Dataset

Gathering the information

Our first step was deciding what information we needed to gather. After some thought and discussion, we decided to focus on eight main factors:

  • Award Category
  • Artist
  • Years Active
  • Piece of Work
  • Number of Streams
  • Number of Sales
  • Billboard Chart
  • Billboard Chart Position

After deciding on our variables, we duplicated them four times so we ended up with five groups: One for the winner of each category, and four for the top four nominees in each category. This allows us to compare the information we gathered about the winning works to the nominees and determine if there are any inaccuracies. This is where the story started coming together. After finalizing our variables, we had to determine what sources to use to gather information. 

The sources we ended up using were:

We started by using the official Grammys website to determine what award categories we would be using and who the winners and nominees were. After determining what artists and works we would be comparing, we moved to Wikipedia to get base information such as years active and potentially, billboard position and/or sales and streams. Knowing we could not rely on the information we gathered from Wikipedia, we began looking for sources that would corroborate the information. 

We started with the billboard site where we could verify what chart and position the work was on and, in some cases, the streams and sales. We eventually had to move to scouring the internet for other sources as it can be difficult to find artists streams and sales. These are factors that are self-reported so some artists do not have the information released to the public. We were able to find various websites that either gave us the information we were seeking or verified what we found on Wikipedia.

What can we learn?

Transforming and Analyzing the dataset

After our information was gathered, we moved on to organizing it. We had a few different datasets throughout the span of this project as our story wrote itself. We began by looking at artist-specific information; such as age, years active, genre, hometown, etc. As our story evolved we shifted to focusing on the awards themselves; Award category, winning work, streams, sales, nominees, etc. As our subject is unique, there were no existing tables we could import for data meaning we had to gather our own data. We did a lot of copy-pasting for things such as years active, genre, and sometimes winning works. As we worked, we began adding new columns such as years active, genre, and billboard chart/position. The year’s active section consists of multiple columns as we had to deal with multiple values. The first column utilizes the MINUS function to calculate how many years total the artist has been in the industry. With some artists, It was necessary to use addition with two MINUS functions as they had a break or hiatus for a number of years. 

Interpreting our Findings

Analyzing the dataset

Once things were organized, we began analyzing the data to find some useful insights. By using the sort and filter transformations, we were able to analyze the data based on specific areas such as name, awarded work, genre, streams, and sorting from greatest to least. By using the sort function, we were also able to make sure we did not count the same artist or work twice when totaling, as this could skew the results. As we analyzed the data, patterns began emerging. As patterns emerged, more ideas for insights appeared and we were able to begin forming our story.

Are the Grammys Rigged?

Building and Visualizing the Story

As we gathered our insights, we realized that our story was forming itself. We narrowed in on the comparison aspect of our insights and decided to look at whether or not the Grammys were rigged. This angle seemed natural as many artists such as Bruno Mars, Drake, The Weeknd, and Eminem have been outspoken on their distaste for the Grammys and how it does not accurately represent the current music hits. The data we gathered paired nicely with this angle as we were able to find several insights to tell our story. Using the data we gathered, we used Flourish to create visuals representing the data. Flourish was quite helpful as neither of us is the most proficient in analytical graphic design. The website allows you to pick the type of visual and will plug in the information you give it, changing the visual to represent it. We ended up being quite happy with the visuals we made and learned a new resource to use in future projects.

Anecdotes

The first anecdote we used mentioned the artists who spoke out against the Grammys, showing that not all artists enjoy the awards. We identified this anecdote after Alexandria watched a video on YouTube where the rapper Eminem spoke out about not liking the Grammys. This led us to research if others had spoken out as well.

By discussing the evolution of music genres, we showed the longevity of some genres compared to others and how they may have influenced each other. As music lovers, we knew that certain genres serve as the base for all modern music so we decided to look into the history to see if it may have impacted the awards.

Using a comparison of social media likes to in-person relationships helps the audience visualize what the relationship between streams and sales is like. Often times people will compare the two as an example of an artist’s success but, while correlational, they should not be compared as there is such a large gap between the achievable numbers. We wanted to demonstrate this to our audience.

Credits:

Alexandria Brown- Spreadsheet Creation and Organization, WritingAva Fishman- Data Gathering and Visuals, Powerpoint Creation

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