Human interest measured by Google search counts and its correlation with celebrity endorsements

Mi (Mimi) Chung
Posted on Feb 18, 2019

Image taken from pexels.com

This Shiny application is a preliminary study on the human interest in celebrities and their endorsements measured by Google search term counts. More specifically, the application focuses on five celebrity rappers with varying lengths of careers and varying levels of fame. This application is a work-in-progress and has potential to become more sophisticated with more data.

The possible applications include:

  • targeting merchandise sales for certain areas in the US
  • targeting shows and appearances for artists
  • gauging the success of celebrity endorsements when they post on social media
  • gauging correlations of things that happen to celebrities and the increase in interest from Google searches
  • Did the celebrity succeed in bringing awareness to a certain cause?
  • Did the celebrity endorsement work, and increase sales in a certain product?

A Google search occurs when a person is interested in the content behind the search term. Using counts of Google searches can be one way to measure the amount of interest, and with time data, it can illustrate the surge of interest in a particular surge term. This Shiny App aims to be the starting point of studying interest in celebrities, their endorsements and the timing of their endorsement posts, and the correlating surge in Google related searches. In this study, I chose rappers with varying degrees of fame and varying lengths of careers and used them to correlate and determine if their endorsements increased interest in their particular endorsements.

This application helps us understand and explore the effects of celebrity endorsements. Google search trends are available to the public and the location of searches dating back 5 years can easily be viewed for any search term. The application compiles the data and allows the chosen artists to be compared.

Screenshot of Rise tab, comparing the lengths and levels of fame throughout each celebrities' careers

In the first data-containing tab, Rise, the interest measured by relative Google search counts for each rapper in the last 5 years is displayed. The graph is interactive, so each search term can be isolated, and multiple terms can be selected for comparison. This graph intends to give insight on the varying levels of interest each rapper has, which illustrates, in time, when and how long each have gotten famous or successful in their careers. The five rappers were chosen based on their varying levels of success and length of careers to provide contrasting comparisons. 

 

Google search counts for search term "Cardi B" over the past five years.

 

Steady increase in "fashion nova" search counts and spike around the time Cardi B posts a Fashion Nova endorsement on social media.

In the following tabs, select endorsements are explored for each rapper, and the location in which the rappers were searched are mapped out along the US. This provides a way to gauge interest for different locations and endorsements. 

To build on the app and make it more sophisticated, with some research, the date and content of endorsements or events in the rappers' lives' can be incorporated into the graphs to explain spikes or lulls in the number of Google searches. For the maps, the tour locations can be correlated to searches coming from those locations.

The possible applications for marketing and level of interest in any Google search term increases. Social media and posts from public figures and celebrities can cause a spike in any level of human interaction with any subject, and this tool is a back-bones beginners project on quantifying human interest.

Link to Shiny App by Mimi Chung

About Author

Mi (Mimi) Chung

Mi (Mimi) Chung

Mimi Chung is a data analyst with experience in the chemical and innovative material science industry as an associate engineer. Previously, she has worked across multiple functions to research, develop and sell electronic solutions. She has experience in...
View all posts by Mi (Mimi) Chung >

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